What It Takes to Be a Data Scientist: Interview with Ravit Jain

Dessie Tsvetkova 3 May 2023 5 min read

Interview with Ravit Jain

Breaking into data science is a long and winding road that requires technical and soft skills and a lot of resilience. We spoke to renowned industry experts and well-liked names in the data science community to discover how and when they knew they had what it takes for a career in the field. They shared their stories and the qualities they developed to succeed.  

In this interview, we introduce you to data science leader Ravit Jain—founder and host of The Ravit Show podcast. He aims to provide data science and AI enthusiasts with the best resources and support for their future careers. Learn more about his work as a data science community evangelist and what qualities he believes every data scientist needs.

Interview with Ravit Jain

Would you please tell us a bit about your background and journey into data science?

My educational background is very different from what I do today. I have my MBA in finance and an executive MBA in investment banking. I was always curious about numbers and data. At my first job in a market research firm, my colleagues and I collected primary data first-hand and secondary data from various sources.

I soon realized data plays an important role in every aspect.

My next move was with a UK-based IT publisher, where I got to work with world-class authors writing оn data science and AI. I was responsible for amplifying the books globally and filling the gap to educate our data science community. This gave me an understanding of what it’s like to build a community.

I’m now the founder and host of The Ravit Show and head community evangelist at AtScale. With over eight years of extensive experience in the field, I’ve been named one of the most renowned leaders in the data community. I often help data and AI enthusiasts with the right resources and provide learning paths for their data science careers. In addition, I help enterprise leaders learn more about the field by interviewing fellow data scientists on The Ravit Show.

I have interviewed over 100 data science leaders, and my podcast has helped more than 90 top-notch data science companies amplify their products and services. As a result of my efforts, I was named among The Top 200 Creators by LinkedIn.

When did you know you have what it takes?

When the data science community starts expecting from you, and you feel equally responsible—that hits you hard and you start doing your best every day.

Seeing that you’ve played a small role in the success of your community members keeps you going and makes you feel special.


I also make sure I’m constantly learning since the data science and AI sphere evolves very quickly. It’s important to learn every day, share that knowledge with your audience, and create content around it.

I’m still a learner and will always be a learner to make it best for my community.

As a data scientist, one needs strong analytical thinking and a lot of technical know-how. What skills did you start with, and how did you develop them to meet the role requirements?

As a data scientist, it's essential to have a strong foundation in programming, statistics, and machine learning.

Data scientists should have expertise in programming languages such as Python, R, SQL, and Java, as they are widely used for data analysis, data modeling, and data visualization. One can take data science courses and training programs to develop these skills.

Additionally, one can work on personal data science projects, participate in hackathons or competitions, and collaborate with others in the field to learn and gain hands-on experience.

Practice is key in developing data science skills, and plenty of resources are available to help you become a proficient data scientist.

Learning is a lifelong process—especially in a field that’s as dynamic as data science. Is there something new you’d like to learn more about or become better specialized in?

Yes, learning doesn’t stop when you’re in the field. You can focus on many areas to improve your skills, such as machine learning, big data technologies, data visualization, natural language processing, and ethics/privacy. Keeping up to date with these areas will help you stay competitive and provide value to your organization.

As an expert in the field, you must have an ample idea of the qualities a person needs for data science. What would you say those are?

A mix of technical and soft skills is important for a data scientist, such as an analytical mindset, programming, business acumen, communication skills, curiosity and creativity, domain knowledge, attention to detail, and much more. 

These are just some of the qualities that are important for a career in data science. But many other qualities can contribute to success in this field, including teamwork, adaptability, and persistence.

As the industry develops, the demand for skilled data scientists grows exponentially. What gives an aspiring data scientist a competitive edge in 2023?

As an aspiring data scientist in 2023, several things can give you a competitive edge in the field, including

  • A strong foundation in mathematics and statistics
  • Knowledge of machine learning algorithms and techniques
  • Experience with big data technologies
  • Strong coding skills
  • Understanding the business landscape
  • Continuous learning
  • Data storytelling

A combination of technical expertise, business acumen, and a commitment to lifelong learning can give an aspiring data scientist a competitive edge in 2023.

We want to thank Ravit for taking the time to provide valuable insights into what it takes to be a data scientist. Check out his podcast, The Ravit Show, where he has interviewed over 100 leaders in the data science community to familiarize data enthusiasts with the field and the role requirements.

Our aim at 365 is to equip you with the tools and give you the necessary guidance to succeed. Designed never to let you give up, the 365 Data Science platform has what you need to develop your qualities and skills.  

Go from a beginner to a skilled professional who creates data-driven value. Study the statistics and probability theory behind data science with online courses led by our renowned instructors, and master sought-after skills like Excel, SQL, and Tableau. Prove you’ve got what it takes with industry-recognized certificates.

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Dessie Tsvetkova


Dessie is a Copywriter at 365 Data Science. She holds a Bachelor’s degree in Creative Writing and is currently pursuing a Master’s in Publishing. Her interest in data science is a natural continuation of her coding experience. In her articles, Dessie aims to make breaking into data science simpler and more accessible so that more people can achieve their professional goals.