Data Scientists and Software Engineers can work hand-in-hand, while some work completely apart from one another, so you can expect to see some similarities and differences between them. A usual company team encompasses a Data Scientist, Machine Learning Engineer, Product Manager, and Software Engineer (a blend of Product and Engineering). Oftentimes, one is already a Software Engineer and will transition to become a Data Scientist and vice versa. Below, I will be describing the skills, goals, differences, and similarities of each role and between each role. The goal of this article is to highlight these characteristics to better understand these positions, how they work with one another, and to start a discussion that can help you decide which role you would like to stay in or change to.

Coding it Forward, in partnership with U.S. Special Operations Command, is piloting the Civic Innovation Corps--a new summer program for mission-driven data scientists and software engineers to create outsized impact in national security. We are looking for mission-driven data scientists and software engineers to spend their summers working alongside executive leadership within U.S. Special Operations Command (SOCOM) and the Department of Defense to support artificial intelligence and machine learning initiatives. The program will run 10 weeks, from June 1 to August 7, 2020. Interviews and offers will be made on a rolling basis--apply as soon as possible.

How do you ensure a smooth hand-off between data science and engineering on ML projects? How do you ensure a smooth hand-off between data science and engineering on ML projects? Excellent question, and one that I've been thinking a lot. At Quora, my data science team works closely with machine learning engineers. Joe Isaacson already provided a great answer to this question, and I will add some of my learnings.