Data Scientist explores new problems and improves products/solutions every day. – Avinash Navlani
Sr. Data Scientist
Q1. Please share your educational and professional journey?
- I have done B.E. (IT) from ITM Gwalior and then M.Tech. in Future Studies and Planning from Devi Ahilya Vishwavidyalaya, Indore.
- Overall 8 Years Experience
- 3 Years industry( currently working as Sr. Data Scientist at Yash Technologies)
- 4 years academics- Asst Professor Devi Ahilya Vishwavidyalaya, Indore;
- 1-year research- Research Assistant IIM Calcutta
Q2. How do you motivate yourself every morning?
Learning and sharing new things, Exploring new problems and improving products/solutions every day.
Q3. Which is your favorite Machine Learning Model to solve real-world problems?
Predicting satisfaction and frustration level of a candidate in an online exam using mouse movement data.
Q4. Where do you want to see yourself after 10 years in your career?
I don’t know because things are changing so rapidly you can’t say about 10 years. but I think I will start my own consulting services in Data Science and AI and maybe Professorship at any institute. Or I am also interested in visiting faculty roles.
Q5. Which one thing do you want to change in yourself and why?
Procrastination, laziness, need more focus
Q6. What do you do in your free time? Do you update yourself in terms of education?
Cricket, Write blogs on data science; sometimes lectures in university
Q7. You had both academic and industrial job experience in your long span of a career. Which one do you like most and why?
Academics because you are dealing with young blood, they have a rebellious attitude and dare to do things that are a must thing to do anything.
Q8. What kind of problems have you faced in your Data Science Domain and how did you remove it?
Coding standards, using Github, explaining things to whom, who have no experience in data science.
Q9. Please suggest good tips to become a professional Data Scientist?
Consistency, honesty, daily reading of maths, stats, programming, cloud and big data.