The world of data has a lot of hazy definitions. This leads to confusion as people use the same terms in a conversation but mean very different things. Three such terms that are often conflated are "analytics," "data science," and "machine learning research." How do we tell the difference between them? And what are the different duties and qualifications of these roles?
Formulatedby's Senior Content Advisor, Q McCallum, met up with Sonali Syngal to explore these questions. Sonali is currently a data scientist at MasterCard and is about to join the team at Expedia. She came to data science from the rather uncommon entry point of economics. In this episode we see that her career path has given her key insights on how to join this field and what are the differences between the various roles therein.(Some listeners may recognize Sonali's voice from a previous episode: she spoke at Data Science Salon in December 2020, where she also joined us for our Coffee Chat. You can check out that episode to learn more about Sonali's take on ML/AI in the world of fintech.)