Importance of Domain Knowledge in Data Science

Opportunity Overview

June 10, 2020; 2:00 pm- 3:30 pm EDT

This is a virtual event.

Naveen Singla, VP, Data Science at Bayer, will lead this webinar highlighting the importance of domain knowledge in data science. Per NYC Data Science Academy, which is putting on the webinar:

Domain knowledge is prominently mentioned as a component of data science. However, compared to its more glamorous counterparts, mathematical modeling and programming expertise, it is quite often under-appreciated.

Through this presentation, Naveen Singla, VP of Data Science at Bayer will highlight the importance of domain knowledge and provide some insights on how to exploit it for successful data science. He will also share his thoughts on how data scientists can acquire some necessary skills to proactively incorporate domain knowledge into their work.

This event is produced by NYC Data Science Academy. NYC Data Science Academy provides award-winning accelerated data science training programs and courses that prepare people for employment opportunities across all industries as data science professionals. Our data science bootcamps, full-time and part-time, have been recognized the Best Data Science Bootcamp for 5 years in a row by

About Naveen Singla

Naveen is a data science executive with more than 15 years of professional experience in the agriculture and finance industries. He is currently heading the Decision Science unit for Bayer’s Crop Science division. During his 10-year tenure at Bayer (formerly, at Monsanto), he has held various other roles including heading The Data Science Center of Excellence and Director of Analytics. Naveen received his Bachelor’s degree from Indian Institute of Technology in Delhi, India, and Master’s and Ph.D. degrees from Washington University in St. Louis, USA, all in Electrical Engineering.

About Bayer

Bayer is a German multinational pharmaceutical and life sciences company and one of the largest pharmaceutical companies in the world.


Opportunity Detail