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Fintech Data Analyst Interview
Questions

30 Questions and Answers by
| Marcie is the principal and founder of CopyHawk, a company that offers editing, writing, and career coaching services. She loves to revamp client resumes so they can land the job of their dreams.

Question 1 of 30

Errors can cost the company clients. How do you ensure your work is mistake-free?

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Fintech Data Analyst Interview Questions

  1. 1.

    Errors can cost the company clients. How do you ensure your work is mistake-free?

      Fintech data analysts need to be fully cognizant of how important it is that their work be error-free. When it comes to the data you're analyzing, it needs to be validated and cleansed so the insights you pull from it are accurate. When you collect data manually, it needs to be entered into the system correctly to prevent problems down the line. Tell the interviewer how you ensure that the work you do is as mistake-free as possible.

      Marcie's Answer

      "By nature, I'm extremely detail-oriented so right off the bat I doublecheck nearly everything I do. Obviously, I know that I have to keep moving and can't spend a ton of time doing this, but it's something that I do automatically. If I enter data into the company's internal system manually, I skim my entries over before I submit them. And when it comes to validating and cleansing the data I'm working with, I never, ever take that lightly. I always put the full effort in because I know that without good data I can't end up with good results. Everything hinges on the data being clean and high-quality; I understand this and always take the time to make sure the data has been thoroughly validated and cleansed before I move on to the next stage in the process."

  2. 2.

    What would you do if you saw that data was missing or suspect?

      There are times when fintech data analysts encounter incomplete datasets. The interviewer wants to know how you would handle this type of situation. If you have encountered this in the past, provide an example and explain how you handled it. It's important to emphasize that you know how important it is that the data you're working with be complete and accurate so your final conclusions are correct.

      Marcie's Answer

      "There have been many times in the past when I've worked on projects and the datasets have contained missing or wrong information. In fact, it happens all the time! There are various methods that can be used to help resolve this issue, including kNN imputation, which I've used before to calculate and fill in missing data. Ultimately, the goal is to work with accurate data so during every project I make sure that any suspect data has been removed during the data profiling and cleansing stages and that any missing data has been replaced before I move forward with the data analysis process."

  3. 3.

    What is the most important skill you've learned in your career?

      There are many different answers you can give to this question. Whichever skill you choose to focus on, be sure to explain why you picked it and why you feel it has been so important to your career. Some possible skills you could choose to talk about include diligence, communication, patience, organization, perseverance, integrity, knowledge about SQL, time or resource management, or interpersonal skills, among many others.

      Marcie's Answer

      "I think the most important skill I have learned during my career is perseverance. The reason being that as a fintech data analyst, I have to stick with what I'm working on despite any obstacles or frustrations that arise in order to derive meaningful business insights at the end. If I give up in the middle of a project because I'm tired of looking at all the data or because the quality of the data isn't as good as I had anticipated, then I never get anywhere. No matter what, I have to keep working on the problem or question until I come to a resolution. If I don't do this, there's no way I can be a great data analyst. But it has taken practice and a commitment to teaching myself to keep going in all cases."

  4. 4.

    Let's say that you're asked to work directly with a client about implementing a new data feed. How would you handle this?

      Most fintech data analysts don't spend much time interfacing directly with clients; that job tends to be left up to customer support, sales, and account management. However, there may be times when it's necessary for you to communicate with a client to resolve a technical issue or to implement a new data-related feature for them. Talk the interviewer through the steps you would take to help the client.

      Marcie's Answer

      "While I generally prefer to be behind my desk, plugging away at my latest data project, I am open to working directly with clients as well. In this type of scenario, I would begin by discussing expectations with my manager and then arranging a call or Zoom meeting with the client in question. During this initial call or meeting, I would find out exactly what the client needs, answer any questions, and provide them with a timeline for when they can expect the feature to be implemented. If it is a straightforward request, I'd hang up and incorporate the project into my workload and look to finish it as soon as possible. If the request requires collaboration with others, I would schedule times to speak with those other analysts. In the end, I would work efficiently and quickly to implement the data feed that the client expects and my manager approves. I always aim to completely satisfy the customer and my manager."

  5. 5.

    What kind of problems do fintech data analysts encounter during projects?

      There are some common issues that fintech data analysts run into time and time again. The interviewer wants to find out if you've experienced these problems yourself during projects and, if you did, how you fixed them. If possible, provide examples and explain what you do to avoid these kinds of issues.

      Marcie's Answer

      "I think part of conducting data analysis is accepting that issues are going to crop up. One needs to try to avoid these problems in the first place, but if they do arise, it's a matter of knowing how to handle them so ultimately your end result is accurate. One issue that frequently comes up is duplicate data entries and spelling mistakes. This is only natural given that people make mistakes when they enter information into databases. I run validation rules to catch and eliminate these kinds of errors. Sometimes the data source isn't reliable, in which case much more time needs to spent cleansing the data. To avoid this, I try to use only reliable and quality sources to obtain my data. Incomplete data creates problems, and another common issue occurs when data is gathered from multiple sources. In this case, it's a matter of structuring the various datasets so they are all compatible and don't cause any delays when I perform the analysis."

  6. 6.

    What is data verification and why is it necessary?

      Fintech data analysts must validate the accuracy, consistency, and clarity of their data at the onset of a project in order to mitigate incorrectly drawn conclusions later on. The interviewer is testing your knowledge around data verification, including how it's performed and why one needs to do it in the first place. Talk them through how you typically validate your data and why you do it.

      Marcie's Answer

      "I always validate my data because I know that imperfect, unvalidated data will likely lead to flawed business decisions down the line. And not only do I make sure to verify the data inputs and values themselves, but I also validate the data model so I don't run into issues later on using my data files in various applications and programs. I typically use validation rules that check for consistency around data type, range, uniqueness, consistent expressions, and null values, in addition to formatting rules that validate the structure of my data. "

  7. 7.

    What is SQL and what kind of experience do you have using it?

      One of the most important skills a fintech data analyst must master is the database language, SQL (Structured Query Language), as it can handle large datasets that Excel can't. Talk to the interviewer about your experience using SQL. If possible, cite an example or two of when you used it successfully during a project.

      Marcie's Answer

      "I began to self-teach myself SQL years ago and later followed that up by taking an online SQL course that provided hands-on training. Since then, I've used it countless times during my career. Mastering Excel was important to be able to manipulate data, but SQL is on a whole other level. I have used it to manage and store data, build databases, change database structures, and relate multiple databases to each other. I honestly don't know how I'd do my job without the knowledge I have about SQL, and I look forward to applying that experience and know-how to this position."

  8. 8.

    What's an area you'd like to improve in?

      This question is essentially a way for an interviewer to inquire about your weaknesses without asking directly. Think of an area or skill in your work life that you know could be improved. Talk about how you plan to learn and gain more experience in this area so you can become a better fintech data analyst.

      Marcie's Answer

      "By nature, I like to work independently so I'd say that one area where I could improve is working as part of a team. I'm happiest when my manager gives me a project and the freedom to complete it as I see fit. This autonomy gives me full control over the outcome of the project, and I like that because I have a strong work ethic and perfectionist tendencies. I definitely get along with my colleagues on a personal level and can work on a team with them as needed. But this is an area that could use improvement since I don't do it all the time and generally prefer to work alone. I know that working with others provides different perspectives that can ultimately make the project process and outcome better."

  9. 9.

    What are your goals for the future?

      Most interviewers are looking for a candidate to hire who will want to stay with the company for some time after they've been trained. This question is their way of scoping out what your future plans are and whether they include staying with the company or moving on. Be honest in your answer but definitely emphasize your loyalty and desire to grow within the company.

      Marcie's Answer

      "As someone who has been in the fintech data analysis field for several years now, I know that this is the career for me and what I want to continue doing. Professionally, my goals include continuing to gain more knowledge and experience so that I can eventually move into a management role. I really look up to my current manager and would love to lead a team of fintech data analysts one day as well. I am coming into this experience with the hope that I will be able to stay with the company for the long term, as long as I'm continuing to grow and learn."

  10. 10.

    What is the worst job you've ever had and why?

      The interviewer is looking for a specific personality type to fill this role: someone who is analytical and detail-oriented, in addition to being someone who doesn't get bored when working with large datasets for several hours at a time. This question helps the interviewer determine if you fit into this mold or not. You will want to avoid talking negatively about a job that you found tedious, particularly one that involves data or numbers, as this will indicate to the interviewer that you will likely get bored within the fintech data analyst position.

      Marcie's Answer

      "The worst job I ever had was when I was a teenager, and I worked as a cashier at an amusement park concession stand. I disliked the job because it was very noisy and busy. It also involved a lot of social interaction, and while I enjoy working with others at times, I prefer to work independently in a quiet atmosphere with fewer distractions. Working with data is something that I really enjoy; I like the mental challenge of it, as well as reaching different milestones throughout the project, like after I successfully validate the data or discover a new trend during the data mining stage."

  11. 11.

    What is your biggest accomplishment to date?

      An interviewer can find out a lot about someone by how they answer this question. Prior to the interview, think about some successes you've had in your life and how you might talk about them. You'll want to choose an accomplishment to discuss that can somehow be related to the fintech data analyst role and that shows positive qualities about you.

      Marcie's Answer

      "Winning a Kaggle competition. So as you can see on my resume, I majored in business so my schooling wasn't really focused on computers or data per se. When I came out of college, I worked in business development, and although I enjoyed certain aspects of it, I felt drawn to data. In my off-hours, I would track different sports and wellness stats in Excel for fun. Eventually, I discovered a website called Kaggle and started competing in their online data analyst competitions. Not long ago, I won my first competition, and I knew I needed to change the direction of my career. I have continued to build my data skills through online courses and competitions."

  12. 12.

    Our primary goal at this company is to make our clients happy. Within this role, how do you plan to provide excellent client service?

      Most of the time, fintech data analysts don't directly interact with clients; however, there's an overriding element of customer service in all roles at a company. The interviewer wants to know what customer service means to you within this role. Discuss what strategies you employ to keep the client top of mind while you do your work and complete projects.

      Marcie's Answer

      "For me, when I spend time validating and cleansing the data I'm working on, my driving motivation is the end customer. I know that if I do a shoddy job in this part of the data analysis process, ultimately the final insights and conclusions that are pulled from the data won't be accurate, which will lead to a lower-quality product on our part. And in fintech, if our product isn't top-notch, this might very well result in a client losing money on an investment and leaving us. So I feel that by doing my best to ensure high-quality, accurate data, I help our company produce the best product possible for the customer."

  13. 13.

    What motivates you?

      If the interviewer were to ask this question to someone in sales, their answer might be money in the form of commissions. A fintech data analyst, on the other hand, would likely be driven by other motivations. Not that earning a good salary isn't important to you, but the interviewer will want to hear that you're also driven by the desire to discover previously unknown trends in the data, to solve business problems, and to finish all the tasks on your to-do list.

      Marcie's Answer

      "I would say that I'm mainly motivated by a job well done. I have a very strong work ethic that was instilled in me by my parents, and when my manager gives me a task I strive to complete it efficiently and in a timely manner so I can earn their approval and know that I did it to the best of my ability. Second, I tend to view data as a puzzle, and I am driven by the challenge of solving the 'puzzle.' So I don't just get my work done for my manager; I get it done so I can rest easy in knowing that I tackled the data and extracted all the insights I could from it."

  14. 14.

    How do you make sure to use critical thinking when working on a project?

      It's vital that a fintech data analyst be able to use data to find answers to questions but this means that the analyst needs to know what to ask in the first place. This means using critical thinking. To be able to succeed as an analyst, you need to be able to think like an analyst. Talk to the interviewer about your ability to think critically; provide examples and explain what steps you take to improve your critical thinking skills.

      Marcie's Answer

      "When I start a project, one of the first steps I take is to think about what problem I'm trying to solve or question I'm trying to answer. This is key. Otherwise, my project won't have a solid direction and who knows where it will end up, which might just waste everyone's time. In order to make sure that I'm thinking critically during a project, I continually ask myself basic questions about it, which helps to keep me grounded and focused when searching for a solution. This also helps me to keep things simple instead of getting carried away with complicated explanations. I also remind myself to think outside-the-box and for myself, rather than to rely on what already exists."

  15. 15.

    Tell me about a time when you had to learn a new method or tool.

      There are always going to be new data analysis programs, tools, and internal processes being introduced. Such is the life of a fintech data analyst. The interviewer wants to know that you are adaptable and able to learn new methods as needed. Give an example of a time when you had to learn something new on the job. Explain how you did so successfully.

      Marcie's Answer

      "When I was in college, I learned how to use Tableau to analyze and mine data, but the first job I got after college didn't use that program. Instead, they used a program called RapidMiner. I had to learn fast and on the job, but I'm happy to report that I picked it up quickly. When questions arose, particularly in the beginning as I was getting used to the new program, I either asked my manager or a coworker for help. I made sure to be polite with my requests and to schedule a good time for them to train. In very little time, I had a clear understanding of the program. I feel confident that I can quickly learn any new program, method, or tool."

  16. 16.

    Tell me about a time when you had to deal with a tight deadline. What did you do?

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  17. 17.

    What kind of challenges do fintech data analysts face?

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  18. 18.

    How do you combat boredom during a long project?

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  19. 19.

    Why should we hire you over other candidates?

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  20. 20.

    Can you tell me about a difficult work situation and how you overcame it?

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  21. 21.

    Why do you want to be a fintech data analyst?

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  22. 22.

    Why are you leaving your current job?

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  23. 23.

    How would your boss and co-workers describe you?

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  24. 24.

    What did you like and dislike about the culture of your last company?

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  25. 25.

    Walk me through the steps you typically take during a data analysis project.

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  26. 26.

    What is the difference between data profiling and data mining?

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  27. 27.

    What program do you prefer to use to analyze data?

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  28. 28.

    What is data cleansing and why is it important?

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  29. 29.

    Do you prefer to work independently or as part of a team?

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  30. 30.

    Why do you want to work for our company?

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