Could you name a few data cleansing best practices that you follow, and how this has helped you become a better Data Consultant?

"In my eyes, data cleansing practices are an important part of my job duties and responsibilities. At the high level, I start with a data cleansing strategy, so I know what the goals and expectations are for the data cleansing initiative. Here is a list of best practices that I follow that has helped me become a better data consultant. 1. Develop a data quality plan - (Create data KPI's, know where data errors occur, determine where the data is coming from, and perform root cause analysis on data health). 2. Standardize customer contact data - (Check important data at the point of entry and create a standard operating procedure). 3. Validate and verify the accuracy of data - (Use manual, web, and email verification). 4. Identify duplicate entries - (Manual and automated systems). 5. Append data for accuracy - (Company name, contact first name and last name, title, phone, email, location, revenue, product lines, company stock, etc.)."

A lot of companies ask their technology employees about why data cleansing matter to them. The answer is simple. Good quality data will help a company identify potential customers, provide better customer service, run better quality sales and marketing campaigns, and know how much they are spending and tracking to determine ROI's. Data Consultants should have expertise with a variety of business intelligence tools like Informatica, Power BI, Cognos, and Microstrategy. All these tools help the company manage data so it can be used within the company for many purposes. What the hiring manager is seeking out of this question is best practices that you follow. Everyone seems to have a way of doing things their way, and because it's their way, it's not necessarily the best way. This is precisely why the hiring manager wants to hear about your best practices method. Has your method made you a better consultant? The best practices method that you share should convey a message of progressive learning and experience gained in the field while being given more responsibilities for larger and more complex projects. Don't forget to list your best practices and the data cleansing strategy that you use as well.

"Since data is so important to an organization, I make the extra effort to understand how data impacts every part of our organization. The fact is that data drives many aspects of a business's operation, and if you don't understand it, you won't know how to plan a strategy around data expectations. As part of my data cleansing duties, I like to sort out the information required so I can do a proper analysis. This is a very important part of the process because it allows me to find anomalies and perform process improvement techniques to remove repetitive information and data quality errors."

Explain what the difference is between Data Mining and Data Analytics, and tell me how you have used both in your recent projects?

"Data Mining and Data Analytics data is compiled by a number of different sources throughout a company. This data comes into the organization in many different forms from different formats, platforms, media, etc. It comes in different shapes, sizes, and venues like social media, social activity reports, customer surveys, emails, weblogs, sensors and bots related to the Internet of Things. I take this data and put it in the correct silos of a data warehouse, then break it down into data points that have relevant and usable data that the business can understand and use it to make business decisions. I was responsible for a data mining project that needed data to calculate operational expenses within the marketing group. They needed to know what it cost the Marketing department to run lead generation campaigns, and what the customer acquisition costs were."

Data Mining and Data Analytics go hand In hand in the world of big data. Data Mining is used to find patterns among large datasets, while Data Analytics is used to test hypothetical models on particular datasets. Over a period of time, you acquire skills that companies see as valuable to their organization. It's these skills that set you apart in the market. As you hone these skills over time, you become good at many different soft skills that accompany the technical skills. Here's where you can use a combination of these skills to articulate a compelling message that explains the differences between Data Mining and Data Analytics. A very important question that might come from an interviewer is how much data do you analyze, and how do you manage that data without risking a security breach. Large scale big data projects use tools like Hadoop as a repository for this data. The reason I mention it is the hiring manger might ask what repository you use to store it, and what your level of confidence using this tool is.

"To me, comparing and contrasting two things like Data Mining and Data Analytics is an exercise that I enjoy a lot. I'm very passionate about data in general. Let me give you an example of these two, and how I used them in my current and past projects. Let's examine the difference between the two, and my experience using both. The Data Analytics process goes into the following steps: Project Definition, Data Collection, Data Analysis, Statistical Analysis, Data Modeling, and Deployment. The Data Mining process is a little different. The steps are Problem Definition, Data Collection, Data Analysis, Statistical Analysis, Data Modeling, Verification and Validation, and Insights. Now for my experience: In a recent project, I collected data from our websites to look at patterns in user behavior and website traffic for all our pages. This data was helpful to the Search Engine Optimization team so they could focus on redeveloping pages that were getting inquires and orders."

When have you worked amongst a diverse group of people?

"I have worked with diverse groups of people most of my career, including my time in University. I am most comfortable, and happy, in this type of environment because it offers a great learning opportunity."

Are you accustomed to working with a very large or diverse team of individuals? Assure the interviewer that you can handle an environment that offers diversity.

"I would say that pretty much every company I have worked for has valued diversity. Working with people from all walks of life help shed different perspectives and identify potential problems faster."

Walk me through your post-secondary education and how it will help you in your career with Keyrus.

"I completed my Bachelor of Applied Technology from Carnegie Mellon University in 2004. During that time I specialized in Data Management and Analysis. I graduated with a 3.67 GPA, one of the top in my class. One of the biggest take-away's from my post-secondary experience was learning how to manage my time while working on multiple projects successfully. I perfected my multi-tasking skills and look forward to bringing those to work for Keyrus."

The interviewer will likely have an idea of your education background from your resume. What they are asking is for you to take a few minutes to bring the experience to life for them! You can talk about your major, or any special academic recognition you may have received. Discuss the strengths gained during your post-secondary training and how those skills will be used in your new position with Keyrus.

"Although I do not have formal post-secondary education, I have taken some courses in customer support, upselling, and a variety of software programs. I look forward to gaining even more knowledge in this role with Keyrus."

Help me understand your standards for success in your last job. Please describe what you did to attain those standards, and if you fell short of expectations, what did you do to remedy the problem?

"There are standards that I follow which have made me successful. I start by putting together a winning team. The way that I select a team is I look for winning attitudes, and quality attributes that fit within our team dynamics. Each team member must possess a willingness to learn from failures, and the eagerness to practice and improve even under challenging deadlines. Each person on my team has to accept ownership of their role, and be accountable for their work. Lastly, each and every person on my team has to be respectful to each other."

If you look at companies of all sizes, you'll find different types of standards for each one of them. A smaller company's standards might differ from a larger one, and this could be based on processes, management and overall operations. They hiring manager in this case would like to hear if you value standards, and if you are involved in setting standards or following them. Ideally you want to explain that you have involvement with both. Start with some basic facts about the standards you have set, and how you have garnered support from leadership and have successfully maintained those standards over a long period of time. It's also important to talk about times you had challenges maintaining standards, and how you were able to remedy issues that came up, and regain the support of your teams. This shows the interviewer your human side, because everyone falls short of expectations at some point, but what you did to remedy the problem will be something they will pay close attention to.

"When it comes to standards, there are many ways to measure success. For me, customer satisfaction is a very important measurable metric. It's my job to figure out what the client is looking for in order to ensure complete satisfaction. I admit, client satisfaction isn't always easy to measure, but once you develop a system that allows them to measure success, you will have a better idea of how to meet their needs. This is a common practice that I developed and use with all my customers. In rare cases where I fell short of my client's expectations, I always examine where things went wrong, and implement a change to immediately right the ship. It could be a number of things like budget, bureaucracy, unrealistic timelines, etc. I document all project cases so I prevent failures in the future."

Describe a time you helped implement a new technology for your client. Did you encounter any challenges, and how did you address them?

"I find that ultimately it's up to the client to make a final decision on whether or not they choose new software. It's up to me to provide all the necessary information needed for them to make an informed decision. There are many factors involved when evaluating new software. I'd like to provide some details about what goes into an evaluation and deployment of new software, and how challenges might be overcome. 1. Strategy and Technology Alignment - what are the goals of the organization, and how is the new software able to meet their business needs? 2. Is there Buy-in from senior leadership or stakeholders - Did management request to look at new software technology, or did it come from an external source? 3. Possible challenges that might come up - Is there anyone in the company that is against implementing new software, and why? 4. Will the new software integrate with existing technology infrastructure - Perform a system analysis to see if additional hardware is needed to support the new software? 5. Team training - How many people within all the departments will need training. My recommendation would be the train-the-trainer method. 6. Who will be maintaining the system once it goes live - Is there internal resources within the company with the proper expertise to maintain the system?"

Anytime you are introducing new technology to a client, you'll have your fair share of people who agree with you, and an equal amount of naysayers in that group too. This is an opportunity to talk about how you were involved in the process from start to finish, and where you encountered challenges, either with the software or personnel and what you did in a problem solver role to resolve those problems. If you look at it, the real purpose of introducing software to an organization is to improve the performance of a business. Give a couple examples of how you were able to get a consensus from department managers and their subordinates to move forward with the implementation. As you're going through these examples, be sure to mention how exactly they will be able to achieve their goals using the new software, and that you'll be able to bring value to the project immediately.

"It is my belief that when a company is exploring the possibility of implementing new software, there needs to be alignment from executive leadership and everyone else that could be impacted by new implementation. This includes the strategic, operational, and tactical perspective of the company. Let me give you an example of how I was able to propose a new software and the approach that I took to address challenges. 1. I showed examples of what the Risk vs Reward would look like after the software was implemented. 2. I inventoried all existing software to see if there were any other software packages that could address current issues without having to buy new software. 3. I gave management a timeline of how long it would take to implement, and how much it would cost. 4. I provided a post-implementation plan that included support and maintenance so that they knew what to expect going forward, and that there weren't going to be any surprises."

Tell me about a time where you made a great recommendation that you think would have greatly benefited your client, but they just didn't like it. What approach did you take to convince them?

"When someone doesn't like my ideas or recommendations, I don't take it personal. I show empathy towards people who may disagree with my ideas or recommended solutions. I understand that some people may not be clear about how the technology or solution works, and how it may benefit them. When it comes to change, it is sometimes difficult to implement change since people like the way they work, and get used to a certain routine at work. One of the approaches that I used to convince them that my recommended solution would benefit the company was to highlight the areas that directly benefited them, and how it would make their daily tasks easier to manage."

It's a challenge when you have to deal with a company that has different opinions and management styles. Depending on whom you are working with, and their role and responsibility, you will likely have to craft a compelling value proposition to clearly show that your recommendations will yield a return on their investment in a relatively short time. Consultants know this all too well. Push back from the client comes from managers who either don't understand the idea, concept or solution, and how it will help the organization. This type of interview question is asked to see how you handle rejection from the client, and if you recommend another solution that might work better. In addition to a compelling value proposition, provide a similar example that you recommended to a client that worked very well and had a good return on their investment.

"Another way I was able to convince this client that they need my recommended solution was that I gave them ownership and involvement in the project very early on so they could see first-hand where they would be able to realize the benefits that directly apply to their department. I made them feel they were an important part of the process. As an outsider (consultant) telling them how I could improve their operations, I know I had to be respectful to their concerns. I avoided confrontation, and took a non-intrusive approach to learn how they worked so I could document and show them exactly where they benefited from my recommendations."

Big Data can be an efficient tool to monitor and grow a business, but can have challenges if not properly implemented. What challenges have you encountered while working with big data?

"I have used Business Intelligence tools like ETL, Informatica, Tableau, QLIK, and Power BI. These tools have helped me shape my knowledge base and career path over the years. I enjoy working with data because it's fun to work with, and I get enjoyment out of it. It has been my experience that big data doesn't always work as advertised. I did have some set-backs on a couple of projects that I managed, and the way I was able to resolve some of the impending issues was I had to re-assess the overall situation, and after doing that, was able to figure out that there was miscommunication between team members and the understanding of the final delivery of the implementation. The issue was the data wasn't being analyzed thoroughly enough to use it as accurate data for the business."

Any implementation if not monitored and managed correctly can turn into a complete disaster. This is especially true of Big Data. When you're dealing with large volumes of sales data, customer data, even confidential data, it makes it that much more important to ensure that you mitigate risk at every level of the implementation process. Having prior experience with successful implementations in the big data space will give you a distinct advantage. A hiring manager wants to hear about the challenges you had with past big data implementations. Managers know that implementations don't always go as planned, so they will be listening carefully to see if you own up to your mistakes or blame others for things that go wrong. It goes without saying, but you never badmouth your company, subordinates or colleagues. A good way to turn this question around is to give an example of a big data implementation that didn't go as planned, but that you were able to get it back on track by re-evaluating the process, the requirements and your team's ability and experience to get this implementation completed successfully.

"A lot of technologies are used simultaneously in the implementation process of a big data project. One area that can't be overlooked is storage. My experience with implementations is that if you have the right infrastructure in place like software-defined storage, compression, duplication, and tiering; it can reduce the amount of space and costs associated with big data implementations. If you don't have these in place before you start the implementation, then you're setting yourself up for failure. I was involved in a project that was delayed for a few reasons. One was that the data wasn't validated, another reason was we were working with disparate data sources, and lastly, we came across organizational resistance (Insufficient alignment and lack of middle management understanding)."

What characteristics or events have contributed towards your success as a leader?

"There is a multitude of factors that have helped me to become a strong leader. First and foremost; I had an outstanding mentor from a young age. Secondly, I have studied leadership at great length. My personality has also contributed to my success as I am a natural coach, teacher, and leader."

Why do you think that you are a successful leader? Talk to the interviewer about the variety of things that you believe have led you to your success.

"Here are some other factors that make a successful leader:- Having a good example, and replicating that example - Working on continual development, both professionally and personally - Being diligent when it comes to fully understanding your business - The ability to make solid decisions, in a timely manner - The ability to delegate when you know you aren't the best person for the task - Maintaining a positive attitude even when times are tough - Admitting when you are wrong, and holding yourself accountable - Keeping your team in the loop on current and upcoming changes"

When have you had to change a major component of your project due to new information being presented?

"I had a large project last month that was nearly complete when the client called to say that the dimensions provided were incorrect. Because of this, our team had to re-do the entire proposal. It took us an additional four days of work but, in the end, the client was delighted with our work, and it resulted in new opportunities with them."

Being able to swivel the focus of your project is a necessary skill for your success in most careers. Talk to the interviewer about a time when a significant change occurred on a project. How did you handle the implementation of the new information?

"Last year we saw new federal regulations come through which affected 80% of our ongoing projects. We had to adjust our plans quickly; however, we were able to deliver a timely product that met federal regulations."

What is your knowledge of imputation? Would you kindly list different types of imputation techniques, and which method you find to be most favorable for your environment?

"When I work on different types of imputation techniques, the goal I want to achieve is what missing information am I looking for, and what am I suppose to do with it. Every company has different rules about imputation policies, and how to handle missing data. In most cases, the software you use defaults to a listwize method of cleaning up unwanted, unused or missing data. It's important to look into how much data you are storing, and how much of that is usable data that the business can use. Some of the methods I use to determine single or multiple imputations are the following:1. Hot Deck Imputation - (A missing value imputed from a random selection). 2. Cold Deck Imputation - (Same as hot-deck, but more advanced and selects from other datasets). 3. Mean Imputation - (Replacing missing values with predicted values). 4. Single Imputation - (Denotes that the missing value is replaced by a value)."

There are multiple imputation methods that can be used for missing data. It comes down to the experience one has using imputation techniques. In most cases, your software by default chooses Listwise deletion. This, of course, all depends on why and how much data is missing. Another approach is imputation which means replacing data values with an estimate, then analyzing the data to see if imputed values were observed. A question like this is posed to help the hiring manager determine your level of expertise with imputation. First, start with an overview of your knowledge with imputation and imputation techniques. They will probably be looking for something along the lines of mean imputation and single or multiple imputations. The way to answer this question with relation to mean imputation is to talk about Regression Imputation, Hot Deck Imputation, Cold Deck Imputation, Substitution, Stochastic Regression Imputation, and Interpolation and Extrapolation. If a question comes up about single or multiple imputations, it's going to depend on unbiased parameter estimates and accurate standard errors.

"Working with missing data can be a challenge for most people, but I find this type of work very rewarding professionally. My role requires me to work with a team of data architects and consultants who provide me with data, and then I apply imputation techniques to cleanse the data so that the company can use it for managing and growing the operations. It is important that I obtain the best quality data before making it ready for the business to use. This is why I apply these types of imputation techniques. 1. Multiple Imputation - (Estimates the values multiple times). 2. Regression Imputation - (Involves replacing missing values with a predicted value). 3. Stochastic Regression - (Same as regression, but adds a common regression variance to the imputation)."

How would your most recent manager describe you?

"In my recent performance reviews and discussions, my manager describes me as a hard worker, motivated and consistent employee. I always strive to exceed expectations when I can. My current manager is happy to speak on my behalf as a positive reference as well."

When you answer this question, draw from your last performance review and a piece of feedback you have received from your most recent boss or coworkers. You do not want to guess what your manager thinks of you. Solidify your answer by referring to the strong employment references you are able to provide.

"My last manager and I had a close relationship. She appreciated all of my efforts when it came to working overtime and taking my work home when required. I believe she would describe me as unique, reliable and energetic."

Would you be willing to work over 40 hours a week?

"I am available for full-time work which is preferably 8-5 Monday to Friday. I am happy to be a team player and work some overtime, as required. Will these hours meet your expectations?"

Before answering scheduling questions, it's important to be clear on the interviewer's expectations. If you haven't had a chance to clarify their scheduling needs, now would be the perfect time to ask! Consider asking, 'What are the scheduling expectations for this position?' If they expect you to work 12 hour days, it would be important for you to know that before you respond with, 'Absolutely! No problem!' You want to be sure that you can meet their expectations. If it turns out their schedule expectations won't work for you, think about what you CAN offer and see if you can meet in the middle. It's much better to discuss these things in an interview than for you to commit to a schedule that won't work for you. Keep in mind that, in most states, an employer cannot demand that an employee work more than 44 hours per week.

"If overtime is required in this role, I am happy to accommodate whenever I can. My only restriction is that I cannot work Wednesday nights as I have an evening course those days."

Describe a situation where a project you were managing failed. What did you learn about this failure, and were you able to salvage or turn it around?

"I was a consultant managing a project with five other team members, and our goal was to develop a loan application app to qualify a buyer for a mortgage. I noticed that we were not able to meet deadlines or present mock designs of the app when the client requested it. I later found several flaws in our methodology and approach which led to delays and cost over-runs. I had to take a step back a re-evaluate exactly what went wrong, and quickly make corrections. Here's what I did to turn it around, and the educational journey it took me through.1.) Take a step back and evaluate how you arrived at this point 2.) Temporarily stop the project 3.) Figure out why the project is failing 4.) Set up a turn-around (war) room 5.) Draft an agenda to go over findings, from quantitative reports to team member interviews 6.) Re-assignment of team member tasks and roles 7.) Gather all notes and project collateral 8.) Set clear objectives, and ask each team member to provide you a work list with specific tasks they are responsible for on the project, and their understanding of the team goals"

As much as we don't like to think about it, sometimes projects fail, and in some cases for reasons beyond our control. Hiring managers realize things do go wrong and projects have to get back on track and show a successful outcome quickly. The more complex the project, the higher the chances are that the project might fail. This question focuses on your ability to bounce back from failure, and what you did to turn it around. Give some thought as to how you might explain why the project failed, and outline the steps you took to turn it around. It is important to list what exactly happened, what lessons were learned, and what you do now to safeguard future projects from failure.

"A failed project can be humbling, and eye-opening at the same time. If not managed and executed properly, it can go horribly wrong. That's why when I put together a team for a project; I religiously follow a methodology that works flawlessly. I've learned to become good at this methodology after a failed project a few years ago. It also made me good at spotting where projects go wrong, and where I needed to make immediate changes. Let me break down what I learned about the failed project, and what I did to turn it around: 1.) What did I learn from the process 2.) How did it affect me and the team 3.) What were the key issues that caused the failure 4.) I found that the key issues were.....Complexity, External Influence, Financial, Organizational, Technology, and Scheduling"

What questions do you have for me about Keyrus?

"Thank you for asking - I do have a few questions. What is top of mind when it comes to filling this role? Also, what types of career growth opportunities would follow this position? And lastly, do you have internal candidates who are also interviewing for this position?"

It's always a great idea to have questions ready for the interviewer. Review the company website and other online resources to ensure the questions you are asking are not mundane, or redundant. The last thing an interviewer wants to hear is a list of items you could have found the answers to from merely watching a video on their company site! Here are some sample questions: - When would you like to have this position filled? - How long has this role been vacant? - Is this a replacement search or a newly created role? - What is your favorite part about working here? - What is the company's primary goal for this position in the next 12 months? - Is there anything from my background and experience that I can clarify for you? - What do you see as the most significant change in this industry over the past three years? - Is there any reason why you would not hire me?

We're a company of innovative thinkers; we rely upon our innovative thinking to solve client problems. Tell me about a time when you came up with a breakthrough idea that was not obvious to others. Describe your idea and how you developed it?

"I've always considered myself an Outside the Box thinker. Settling for the norm has never been my working style. I always work with the expectation that my idea will serve many purposes, and bring value to our customers. One example is when I came up with an idea to train the trainer at multiple locations via remote video conferencing. This idea was well received, and was implemented at over 50 locations worldwide. I came up with the idea because I was responsible for training multiple divisions and didn't have the budget to fly everyone in from multiple locations for the training sessions."

Innovation is the cornerstone of any successful company. If you show me a highly successful company, I will show you people within that company that were innovative thinkers. Great examples are Steve Jobs from Apple, Bill gates from Microsoft, and Jeff Bezos of Amazon just to name a few. The hiring manager is posing this as a two-part question to see if your response is clear, concise, and related to the question. Stay on point with your response, because that's what they're looking for. Think about this question for a minute to dissect what they are asking. They are a company of innovators.....which means, will you fit into their culture and be able to come up with ideas that will be innovative. They will be listening attentively to how you articulate your message about your breakthrough idea. Walk them through how you came up with the idea, what your thought process was, how you got approval to move forward, and how you executed on the idea.

"I was working on implementing a friendlier looking graphical user interface solution for a financial services client. The inspiration came from the feedback I received from people at the client site complaining about processing transactions on a mainframe computer that wasn't much fun to work with or look at. They were used to the dreaded Green Screen on a mainframe, but my solution had a Windows look and feel which they liked quite a lot."

Your customer wants you to explain the benefits of the Big Data model you developed, how do you communicate the insights they can use for their business?

"My expertise has been in Data Analysis, so Big Data to me was a pretty flat and easy learning curve. When you're working with large volumes of data, you need to make sure that the data is scrubbed (clean) so that the information can be interpreted by the organization so they can use that data to make better business decisions. I was able to do this by using data warehouse applications that broke down the data in smaller manageable groups that had relevant information about each customer or prospect. Based on my knowledge, there are a lot of benefits that a company can get out of big data. Here's a short list that I have compiled based on my experience:1. Ability to acquire, extract, modify, analyze, and blend the data with various business intelligence tools in order to get the information you need to run your business. 2. You can evaluate risk by a portfolio of products or services. 3. Be able to customize customer experiences. 4. You can identify important information or performance data to improve decision making. 5. Real-time forecasting and monitoring across company-wide locations, divisions, and business units. 6. You can monitor sales and marketing campaigns, and track customer purchasing habits."

Everywhere you look in corporate America; you will find Big Data. It's fast becoming one of the most important facets of a business's operation. Big Data is used for data analytics and data management. If you want to know if your company is profitable or losing money, big data analytics can provide that. If you want to see what product sold best in a specific region of the country or world, big data analytics can provide that information. It's like having a dashboard with multiple screens in one that shows the performance of your company, people, processes, etc. Everyone talks about this concept, but very few can articulate the benefits of big data and how it can help a business. This is especially true for data consultants who are new to big data. Depending on the level of experience that you have, one of the most important areas that you should focus your response on is highlighting the insights that the customer is going to realize when they implement a big data solution. The interviewer is interested in hearing about how you present benefits to the customer in a way that connects with the customer's pain and adds value to the company. Effective communication is key here. They might ask for a hypothetical scenario where you clearly presented a case for big data and it's benefits. It would help to mention that they would be able to calculate metrics for data gathered from multiple sources like social media, customer profile data, company website, etc.

"In years past when I worked with data management tools, it was systems like ETL and Data Warehouses that I used to compile and structure data that the business could use. These were typical Business Intelligence solutions at the time, but they weren't as robust as they are now. My responsibility was to extract and cleanse data so I could present it in a way that was easy to understand to a non-technical person. Having a strong analytical background helped me to analyze different forms of data so I could optimize and index data structures in order to present the many benefits that big data has to offer."

When you suffer a setback, how does that emotionally affect you and your work?

"Experiencing a setback is always disappointing, and can be a bit disheartening, but I understand that it happens from time to time. If I experience a major setback, I will take a few moments to debrief with my manager and discuss what I could have done differently. Then, I move on!"

Everyone handles the stress and disappointment of setbacks differently. Discuss with the interviewer how you typically cope with delays in the workplace.

"Setbacks happen for a reason, and they do not affect me emotionally in the least. I am a very pragmatic thinker and stay focused despite the challenges that come my way."

Have you ever broken a confidentiality agreement?

"I never have, to my knowledge, broken a confidentiality agreement. Despite my reasons for leaving a position, I would never choose to hurt a previous employer in any way."

Companies will have confidentiality agreements for a variety of reasons. These could be to protect their trade secrets or to ensure that you do not bring clients over on the occasion that you leave their company. Talk to the interviewer about your thoughts on confidentiality agreements.

"I understand the importance of confidentiality agreements and would never breach a sensitive agreement like that."

What are your salary expectations?

"Currently, I earn a base salary of $45,000 per year plus a potential 20% annual bonus. Last year my earnings were $52,000, and I would like to stay in the same range or slightly higher."

The best way to discuss your salary expectations is to use your current earnings as an example. Be open, and honest. Transparency is the best choice when salary based questions arise.

"I am currently making $100,000 per year with two bonus opportunities. I am looking for compensation that is aligned with the role and provides an opportunity for growth."

When designing a machine learning model, what in your opinion is more important, model performance or model accuracy, and why?

"In my opinion, I believe that model performance and model accuracy have an equally important role to play in Machine Learning. When I work with model accuracy, I understand that the better the data is the better the outcome of the results will be. This data provides better predictions and insights that deliver more business value, and by optimizing model accuracy, it mitigates cost as well. I find this to be important at many levels of the organization because while there is a point of diminishing returns, the value of more accurate models corresponds to profit increases for the organization. When I use the Machine Learning model performance method, I start with a baseline model, and then I determine if the model skill is relative, and then assign a score to it. This method, in my opinion, is slightly better, but not by much. The biggest reasons are; mean outcome values for a regression and classification problem, and better input and output for forecasting."

Machine Learning as we know it is revolutionizing the way we buy, the way we live, and the way we work. Companies everywhere use machine learning models to improve the way they do business. It helps companies make more precise business decisions based on the data they have. When developing a machine learning model, one has to rely on data that can be used to develop new products, and provide insights into business operations and decision making processes. Interviewers ask this question because they are interested in a few different things from you. The first thing is your opinion on the importance of model performance and model accuracy. Your opinion should not heavily discount one over the other since they're interested to hear if you have worked with both, and why you have a preference over one or the other. Give an example and explanations of why you think one is better than the other, and detail the features, processes or techniques that you feel work better for you or the company. You could mention that model accuracy is used for identifying relationships and patterns between variables in a dataset. Model performance can also be mentioned as calculating current values based on a prediction and comparing the model's performance.

"Predictive models as a whole are exciting to work with since you're dealing with both model accuracy and model performance. In my career working with data, I find that a machine learning model is directly correlated with the quality of the data provided by the sources in a company. As mentioned earlier, I believe both methods provide value to an organization. Some of the data quality issues I've come across using model accuracy are missing or erroneous values in a data set, categorical values that don't work well with textual values, data dimensions that are required to be reduced due to size, and lastly issues with scaling values and features.""

Our clients have high expectations of our work, tell me about a time you worked with challenging time constraints, but were still able to exceed client expectations.

"Almost every project will have time sensitivity challenges and deadlines that need to be met. I am very mindful of these things, and take the appropriate steps to ensure projects are planned properly with the appropriate amount of resources, technology, and approvals throughout the process. The way that I start and execute on a project is always with a project plan that serves as a roadmap for success. If I am to avoid time constraints and other challenges, I clearly identify the deliverables, and follow through on the most efficient way to produce them. In order to avoid distractions, I take a close look at design and test times, project risk, team focus, and management involvement so that we minimize delays from the executive level."

If I only had more time. I hear this all the time. It's a fact of life in the business world. Being prepared for situational questions that ask about project planning, resource planning, expectations, delivery, and how you anticipate distractions will show the hiring manager that you have meticulously planned and know each step in the process. Your answer should reflect the steps you take to resolve a problem, or minimize risk so problems don't occur. Walk the interviewer through one of the steps in the process, and detail how you address time constraints specifically, and how you are able to still meet client expectations. Detail this response with how you set up a project plan, the step-by-step approach, and why everyone needs to follow the process in order to avoid delays, and to deliver on time.

"When I start a project, there are a number of tasks and milestones that I consider very carefully. The most important one is identifying risks up front to avoid surprises. I take a systematic approach to each step and phase of the project. It has been my experience that setting quality expectations in advance sets the tone for a much more favorable outcome for the project. Keeping a focus and not deviating from the original plan is important for meeting milestones and expectations. I understand that changes happen, and change management needs to be addressed if this happens. If or when change happens, we refocus the project using rapid application development RAD to stay on schedule so the delivery date of the project doesn't change."

A client wants to implement a new software system that was recommended by a different division of the same company. How do you evaluate it to ensure it's the right choice?

"I've been in similar situations like this before, and have consulted clients on what needs to be considered before a new software implementation can take place. In a consulting engagement, a proper discovery and background must be conducted on the business. This step is absolutely critical. If you don't understand why the customer is asking you to evaluate new software for their business, you'll miss the most important part of why you are evaluating the software. My experience has shown that if you find the compelling event or pain point that's prompting them to look at a new system, you'll know if it's the right choice for them."

It's not uncommon for many corporations with multiple locations or divisions to have different computer systems and networks that don't necessarily talk to each other. They may share a few common systems that allow them to communicate with other locations or business units to conduct business as usual. Since companies that are decentralized have systems, networks, and/or software that could differ from other locations, hiring managers will ask how you will gather information, who you will talk to, the method you will use to evaluate the new software, and how you will arrive at a decision to recommend or not recommend the software. Giving an example or short checklist of what you will cover in the evaluation process will be important.

"There's a step-by-step process that I follow that yields great results when it comes to evaluating new software for a corporation or division. As mentioned earlier, a proper discovery of the business operations is critical. Let me walk you through the process I use as part of the discovery: 1. Have the client explain the need for the software and the problems they expect it to solve for them. 2. Ask if they have the technical expertise internally to maintain the software, or do they plan to outsource the maintenance for the software to an IT Consultant or firm. 3. Do an assessment of their current technology infrastructure to see if they can support this new software and if they need to purchase additional hardware to run the system. 4. Find out how many people would potentially need to be trained on the new software, starting with key personnel (Administrators/Power Users) managing the system. 5. Provide a comparison of similar software with similar features, benefits, along with a breakdown of pricing for each software solution, and what it will cost in the long run. 6. Ask when they want you to submit a report on your evaluation."

Tell me about a time that you were assigned to manage a data analytics project. Walk me through the step-by-step process that you used to kick-off this project?

"Managing a project can come with challenges if you don't take the right steps to prepare and execute properly. There are certain steps I take to ensure that the preparation is done even before kick-off is underway. The pre-prep of a project is a very important step before the actual kick-off. The main elements of the project pre-prep are having the right team members in place with the appropriate skills, and communicating tasks, deadlines, milestones, and clear objectives. Once that is done, I proceed to the data analytics modeling steps. Here's how I prepare, and the steps I take to ensure a successful project kick-off. 1. Define expectations and results - (Requirements gathering sessions with identification of expected results). 2. Team assignments and responsibilities - (Clear vision and outcome of project, and assessment of team capabilities). 3. Project Management - (Monitor and manage project with clear milestones). 4. Organizational Management - (Establish processes, activities, change requests and deliverables). 5. Data Governance - (Management of data quality, security, performance, team, integrity, and priorities)."

Everyone has their own unique style of managing and kicking off a project. What we'll examine here is a commonly used step-by-step process that most people use as part of their preparation to get a project started. The main purpose of an interviewer asking these questions is to understand better your approach to a data problem and what your process is to ensure the success of the project. A good way to get this started is to understand the objective and goal of the project. Before you start the data modeling process, you'll need to have a complete and accurate dataset and make sure that the entire team has specific tasks for what they will be doing throughout the data modeling exercise. During the interview, you will likely be asked what tools you will use as part of the step-by-step process, how you will validate the data, and the method you will use to track the output results.

"There's something special about kicking off a project. Being able to oversee and deliver a successful project is very rewarding. It's not only seeing the project through to its completion but managing it after it's kicked-off. Yes, I do have a process that I follow, and I do monitor the project from the infancy of the concept phase to the realization of what the project will look like when it is delivered to the business unit. I feel it's important to see the vision and realization of how the project will come together even before it gets started. I've had this unique skill for a long time, and it's helped me start and complete a number of projects with data at the center of them."

What part of this career brings you the most stress?

"The part of my career that brings me the most stress is when the schedule is running behind due to lack of hustle on my teams part. I like to be on time with my schedule to ensure that my clients are assisted properly."

Stress can often be a regular part of the day to day work experience. Talk to the interviewer about which areas of your career are the most stressful. Ensure that your answer does not include a factor that would make you appear unfit for the position. (IE: a bus driver should not find driving to be the most stressful part of the job).

"I probably bring myself the most stress because of my drive and desire to be/do the best I can be. I manage this by focusing my energy on productive activities that are good for my career."

Describe to me your ideal employer.

"My ideal employer is one that brings charisma and passion to their work. I work best with organizations who have a penchant for learning and promote their employees based on performance."

A job search isn't just a one-sided hunt. You must also feel as though this is a good fit for yourself. Tell the interviewer what your ideal employer looks like. Be specific and be sure to keep the conversation positive. Avoid speaking poorly of any previous managers or organizations.

"Here are some other ways you could describe a great employer. A great employer will: - Pause to have fun now and then but also know when to be serious - Treat everyone fairly, and equally - Offer rewards for great work - Offer a continually challenging environment - Offer flexibility and understands that personal situations come up from time to time - Encourage a collaborative workplace"

When dealing with data, in your opinion, is it better to have too many false positives, or too many false negatives? Please explain.

"The way I approach false negatives and false positives is to form a null hypothesis which leads you to try and reject it, thus giving me a positive result. I know that data scientists don't like the notion of swapping hypothesis, but they do give us situations where arriving at a false negative is not ideal. I've heard cases where false positives have had bad outcomes because of how the data was analyzed. Everything is not so Black and White. There are examples that have a hypothesis that cannot be switched due to the nature of science and law, which shows that errors are interchangeable. It comes down to how you design and research your study."

There has been much discussion and speculation about false positives and false negatives, and not all data scientists are in 100% agreement with what is interpreted as a false negative and false negative. Let's say for example you were diagnosed with not having a disease, but after numerous tests, it was verified and confirmed that the disease was in fact still present. That would be considered a false positive. If on the other hand you were diagnosed with a disease, but found out later that you didn't have a disease, which would be considered a false negative. In this type of interview situation, the hiring manager is looking for two things. Your opinion and explanation about false positives and false negatives when it comes to dealing with data management. Data results can be misleading at times, and you need to be able to explain why this is the case, and in your opinion how the data is viewed negatively or positively based on whatever tests were run to arrive at the result from the data. It would help to offer your perspective to the interviewer on the way you determine whether you think it's better to have too many false positives or too many false negatives to sort out.

"Although false positives and false negatives have been debated on probably every topic available, it has been my experience that having too many false negatives over false positive results have been better for our work environment. Especially when you're dealing with something as sensitive as data. There are times when I run QA or validation tests on data, and depending on what we're looking at, we could get a false positive or false negative. That's why having too many false negatives helps weed out the false positives."

The way we approach clients in our business is we identify client needs and recommend solutions to their needs. Tell me about a time when your knowledge and expertise allowed you to make a recommendation to resolve a problem or address a pain point?

"I've been a firm believer that the customer is always our highest priority and that I need to be the eyes and ears of the customer. With that said, there some examples I can share that will hopefully resonate with you. I typically ask what solutions have been proposed in the past, and how they have worked. Are there metrics to track the success or failure of past efforts? Having data to review helps me understand the process and approach previously used. Knowing the team makeup, and what methodology they used will also give me a deeper insight into what they were thinking. I like to conduct a voice of the customer survey, which I believe adds tremendous value to this campaign. Lastly, it's important for me to analyze the cause & effect relationships from the customer surveys, because It reveals a lot of underlying issues like task failures, root cause problems, and how good or bad the data is."

The is a classic example of the hiring manager asking you to role play your response. The way it works is the hiring manager asks you to role play as the consultant, and he/she is the client who asks you to give them a pitch about why your company is a firm that they need to work with. There are a few ways to make this role play work in your favor. Here are a few examples you can use in a response. 1. Act as a problem solving adviser that can find and recommend solutions quickly, 2. Tell the client they have accessibility to you and other team members as needed, 3. Point out the benefits that they will get when they hire your company, 4. Share some examples of successes from companies of a similar industry, size or market.

"My recommendations would be based on what the customer wants and how well they articulated the deliverable. If, for example, the client wanted something that resembles a ketchup bottle, but the team delivered a salt shaker, that would indicate a miscommunication of what the client requested. My approach would be to closely dissect the customer requirements, then build a mock-up of what they requested, and have them review for approval before going to the next phase of development. After this phase is approved, I would do testing and debugging before presenting it to the customer. Mapping the customer journey is a visualization process a customer goes through and tracks each step along the way with the vendor, so everyone is on the same page."

Keyrus Interview Questions

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1. Could you name a few data cleansing best practices that you follow, and how this has helped you become a better Data Consultant?
2. Explain what the difference is between Data Mining and Data Analytics, and tell me how you have used both in your recent projects?
3. When have you worked amongst a diverse group of people?
4. Walk me through your post-secondary education and how it will help you in your career with Keyrus.
5. Help me understand your standards for success in your last job. Please describe what you did to attain those standards, and if you fell short of expectations, what did you do to remedy the problem?
6. Describe a time you helped implement a new technology for your client. Did you encounter any challenges, and how did you address them?
7. Tell me about a time where you made a great recommendation that you think would have greatly benefited your client, but they just didn't like it. What approach did you take to convince them?
8. Big Data can be an efficient tool to monitor and grow a business, but can have challenges if not properly implemented. What challenges have you encountered while working with big data?
9. What characteristics or events have contributed towards your success as a leader?
10. When have you had to change a major component of your project due to new information being presented?
11. What is your knowledge of imputation? Would you kindly list different types of imputation techniques, and which method you find to be most favorable for your environment?
12. How would your most recent manager describe you?
13. Would you be willing to work over 40 hours a week?
14. Describe a situation where a project you were managing failed. What did you learn about this failure, and were you able to salvage or turn it around?
15. What questions do you have for me about Keyrus?
16. We're a company of innovative thinkers; we rely upon our innovative thinking to solve client problems. Tell me about a time when you came up with a breakthrough idea that was not obvious to others. Describe your idea and how you developed it?
17. Your customer wants you to explain the benefits of the Big Data model you developed, how do you communicate the insights they can use for their business?
18. When you suffer a setback, how does that emotionally affect you and your work?
19. Have you ever broken a confidentiality agreement?
20. What are your salary expectations?
21. When designing a machine learning model, what in your opinion is more important, model performance or model accuracy, and why?
22. Our clients have high expectations of our work, tell me about a time you worked with challenging time constraints, but were still able to exceed client expectations.
23. A client wants to implement a new software system that was recommended by a different division of the same company. How do you evaluate it to ensure it's the right choice?
24. Tell me about a time that you were assigned to manage a data analytics project. Walk me through the step-by-step process that you used to kick-off this project?
25. What part of this career brings you the most stress?
26. Describe to me your ideal employer.
27. When dealing with data, in your opinion, is it better to have too many false positives, or too many false negatives? Please explain.
28. The way we approach clients in our business is we identify client needs and recommend solutions to their needs. Tell me about a time when your knowledge and expertise allowed you to make a recommendation to resolve a problem or address a pain point?

Keyrus Interview Questions

1. Could you name a few data cleansing best practices that you follow, and how this has helped you become a better Data Consultant?

2. Explain what the difference is between Data Mining and Data Analytics, and tell me how you have used both in your recent projects?

3. When have you worked amongst a diverse group of people?

4. Walk me through your post-secondary education and how it will help you in your career with Keyrus.

5. Help me understand your standards for success in your last job. Please describe what you did to attain those standards, and if you fell short of expectations, what did you do to remedy the problem?

6. Describe a time you helped implement a new technology for your client. Did you encounter any challenges, and how did you address them?

7. Tell me about a time where you made a great recommendation that you think would have greatly benefited your client, but they just didn't like it. What approach did you take to convince them?

8. Big Data can be an efficient tool to monitor and grow a business, but can have challenges if not properly implemented. What challenges have you encountered while working with big data?

9. What characteristics or events have contributed towards your success as a leader?

10. When have you had to change a major component of your project due to new information being presented?

11. What is your knowledge of imputation? Would you kindly list different types of imputation techniques, and which method you find to be most favorable for your environment?

12. How would your most recent manager describe you?

13. Would you be willing to work over 40 hours a week?

14. Describe a situation where a project you were managing failed. What did you learn about this failure, and were you able to salvage or turn it around?

15. What questions do you have for me about Keyrus?

16. We're a company of innovative thinkers; we rely upon our innovative thinking to solve client problems. Tell me about a time when you came up with a breakthrough idea that was not obvious to others. Describe your idea and how you developed it?

17. Your customer wants you to explain the benefits of the Big Data model you developed, how do you communicate the insights they can use for their business?

18. When you suffer a setback, how does that emotionally affect you and your work?

19. Have you ever broken a confidentiality agreement?

20. What are your salary expectations?

21. When designing a machine learning model, what in your opinion is more important, model performance or model accuracy, and why?

22. Our clients have high expectations of our work, tell me about a time you worked with challenging time constraints, but were still able to exceed client expectations.

23. A client wants to implement a new software system that was recommended by a different division of the same company. How do you evaluate it to ensure it's the right choice?

24. Tell me about a time that you were assigned to manage a data analytics project. Walk me through the step-by-step process that you used to kick-off this project?

25. What part of this career brings you the most stress?

26. Describe to me your ideal employer.

27. When dealing with data, in your opinion, is it better to have too many false positives, or too many false negatives? Please explain.

28. The way we approach clients in our business is we identify client needs and recommend solutions to their needs. Tell me about a time when your knowledge and expertise allowed you to make a recommendation to resolve a problem or address a pain point?