By Saeed Mirshekari

Jan 7, 2023


If you are considering a career in data science, there is no better way to do so than by asking experienced data scientists questions. This is especially true if you are a beginner in the field. In this article, we will look at some of the most important questions that you should ask your mentor regarding your career and his/her field of expertise.

Technical Questions

As a data scientist, you may have technical questions that are specific to your job. You can use these questions to learn more about the tools and techniques your mentor uses in his or her work. For example:

  • What is the most important thing you have learned from your mentor?
  • What are the tools and techniques that you use to achieve your goals?
  • How do I learn these tools and techniques?
  • What are the most important things I should know about my industry?

Click here to connect with Data Science mentors 1-on-1 in just a few minutes!


The industry is the first thing you want to ask your mentor about. What is the industry? How does it differ from others? Which industries are related and how do they interact with each other?

You should also ask about challenges and opportunities in this industry. For example, in banking, there may be a lot of regulations for data science teams working with financial data that make it challenging for them to deploy some of their ideas. However, on the flip side, banks have a lot of money at stake so they can afford to pay more if you come up with something good!

Day to day work

You may be at a career crossroads and looking for some direction. Maybe you're planning to go back to school and want to know what careers are available in your chosen field, or perhaps you've just graduated from college and are wondering what kind of job prospects are out there. Or maybe you're happy with where you are right now but want to make sure that things stay interesting enough so that your job doesn't feel like drudgery. Whatever the case, one valuable way of finding answers is talking with people who have similar careers or experiences as yours--but preferably those who have been working in those fields longer than yourself (ideally they will also be older than 30). This is especially true when it comes time asking these questions: What do they do exactly? How much variety is there in their daily tasks? How has their work changed over time? And how does all this inform their overall happiness with their jobs?

Soft skills

For many people, soft skills are the most important part of their job. Soft skills are not technical, they're the human side of your job. They are how you interact with your manager, coworkers and clients on a daily basis and can make or break a project.

Soft skills include:

  • Communication - Being able to communicate effectively is one of the most critical skills for any successful Data Scientist! Your ability to collaborate with others depends on good communication. Work hard at being clear about what you think and feel in order to build trust among your colleagues (and clients). Use active listening techniques when working with others so that everyone feels heard and understood. Don't forget that everything has its place—give yourself time each day (even if just 15 minutes) for quiet reflection so you don't get overwhelmed by all that needs doing!

Ask your mentor these questions!

A mentor can help you learn the ropes, get started on your career, and solve problems. Mentors can also network with you and help you find opportunities.

Here are some great questions to ask a data scientist:

  • What is the best way to approach a problem?
  • Who is an expert in this area? Who do I need to talk to?
  • How did they get into this field? Can I shadow them for a day or two to learn more about their processes and background knowledge?

Important advices

Your mentor should be able to give you advice on how to stay curious about data science, how to ask questions and be open-minded, how being passionate and humble will help in your career, and how honesty is the most important quality for a data scientist.

If you do not have a mentor yet, consider reading this page.


We hope that the questions above will help you to build a better relationship with your mentor. It is important to remember that these are just examples, and there are many more questions you could ask. The more you know about your work and how it fits in with what's happening in the industry, the more prepared you'll be when it comes time for promotions or raises!

  1. What inspired you to pursue a career in data science, and how did you get started?

  2. Can you share some key lessons you've learned throughout your journey in data science?

  3. How do you stay updated on the latest trends and advancements in the field of data science?

  4. What advice do you have for someone just starting their career in data science?

  5. Can you tell me about a challenging project you've worked on and how you approached solving the problems that arose?

  6. How do you balance the technical and business aspects of data science in your work?

  7. What programming languages and tools do you find most valuable in your day-to-day work, and why?

  8. In your experience, what skills are crucial for a successful data scientist, beyond technical expertise?

  9. How do you approach communicating complex technical findings to non-technical stakeholders?

  10. Can you recommend any books, courses, or resources that you've found particularly helpful in advancing your
    skills as a data scientist?

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About O'Fallon Labs

In O'Fallon Labs we help recent graduates and professionals to get started and thrive in their Data Science careers via 1:1 mentoring and more.

Saeed Mirshekari, PhD

Saeed is currently a Director of Data Science in Mastercard and the Founder & Director of O'Fallon Labs LLC. He is a former research scholar at LIGO team (Physics Nobel Prize of 2017). Learn more about Saeed...

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