The DataHour: How to Transition into Data Science?

Dear Readers,

I appreciate you coming onto our platform and expanding your knowledge. I am sure, by now, some of you must be interested to make a transition into the Data Science industry as it’s one of the most host-selling jobs (if we can put it that way :D). So, this DataHour session is dedicated to all our readers who have been thinking to take a leap of faith and make this transition happen!

Sutirtha Chakraborty is currently working as Head at Global Data Science & Analytics, Abbott. And, he is ignited to share his knowledge and personal experience in the world of ‘Data Science’ with you all. I know most of you will have certain apprehensions about it and it’s all very understandable. So, leverage this opportunity and ask all your doubts pertaining to the transition that you have been thinking through!

BOOK YOUR SEAT NOW! 🛋️

About the DataHour

Data Science is the new umbrella term for all ‘Data Analysis’ related work in the Analytics space across all industries. Its exponentially growing popularity over the last few years has been primarily fueled by the massive growth in the amounts of data generated regularly in these industries along with an unprecedented improvement in the computational tech infrastructure and innovation of various transformational methods that have solved some of the most complex real-world problems at scale.

This has brought along a vast number of interesting and lucrative job opportunities across all these industries, striking a deep interest in people with a wide variety of academic backgrounds to switch to a Data Science job. But this transition is not easy at all – in fact, it is very hard, especially for those people who don’t come from a traditional Statistics or Computer Science background. 

In this DataHour, discover how you can successfully transition into a Data Science job and build a solid career profile in it.

Prerequisites: A genuine interest in Data Science

Who is this DataHour for?

• Students & Freshers who want to build a career in Data Science
• Working professionals who want to transition to a Data Science career

Speaker

Sutirtha Chakraborty

Head – Global Data Science & Analytics, Abbott

Sutirtha has 20+ years of experience in Statistics and Machine Learning, Healthcare Research & Development and Product Management. Prior to joining Abbott, Sutirtha was associated with Neference Labs Private Limited as a Senior Director of Engineering (AI/ML). In the past, Sutirtha has also worked with GlaxoSmithKline and Novartis as a Data Science Leader.

Sutirtha served as a Postdoc in Statistical Genomics at the Harvard University and Dana-Farber Cancer Institute. He has a PhD in Biostatistics from the University of Louisville, KY, USA, an MSTAT in Applied Statistics and Data Analysis from the Indian Statistical Institute, Kolkata and a BSc in Statistics (Hons) from the Presidency University, Kolkata.

Conclusion

Grab this fantastic opportunity by registering here for the DataHour Webinar. If you’re attending this session and have some preliminary questions about this topic, please send them to us at [email protected], or you could ask directly to the speaker during the session.

If you missed our previously conducted ‘The DataHour’ series, head to our YouTube Channel and check out the recordings. Read the synopsis about the previous held DataHour sessions on our blog here.

Connect

If you’re facing any difficulty registering or wish to conduct a session with us. Then, get in touch with us at [email protected].

BOOK YOUR SEAT NOW! 🛋️