Meet Our Alumni, Dr. Mike P. Cohen: Three math tracks: each alike in dignity? | Department of Mathematics

Meet Our Alumni, Dr. Mike P. Cohen: Three math tracks: each alike in dignity?

Event Information
Event Location: 
GAB 461
Event Date: 
Monday, November 7, 2022 - 4:00pm

Dr. Mike P. Cohen graduated from UNT in 2013 with a PhD in Mathematics. Dr. Cohen's career pathway is unique and successful: He was an Assistant Professor in North Dakota State University and moved to Carleton College (one of the top 10 liberal arts colleges in the US). Currently, Dr. Cohen is working as a Lead Data Scientist for C.H. Robinson, which is a third-party logistics company (largest in the USA, Minnesota based). He will talk about his academic job-hunting experience and/or how he transitioned to a career in industry.

This special colloquium will follow a unique format: a short talk follows by a panel discussion. The PhD graduate panelist is Ms. Jill Kaiser and the moderator is Dr. Kiko Kawamura. Cookies and coffee/tea will be served in GAB 473 prior to his talk.

Let's meet Dr. Mike Cohen to ask how studying pure mathematics helped him to achieve his career success and finding a happy life!

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Title: Three math tracks: each alike in dignity?

Abstract: Many math Ph.D. seekers hope to find a career as either (1) a research mathematician at a doctoral granting institution; (2) a teaching professor at a liberal arts college; or (3) an industry mathematician at a Fortune 500 company. Nine years after completing my Ph.D. in math at UNT, I find myself in the weird, but perhaps not uncommon, situation of having experienced all three! I'll share some details of how I wandered through three very different environments (academic jobs at North Dakota State University and at Carleton College, and through to my current position as a data scientist at C.H. Robinson) and describe what I perceive as strengths, drawbacks, and major takeaways from these disparate career paths. The main audience for this talk is UNT math grad students, for whose benefit I will emphasize frankness, even around such shocking taboo topics as: research fatigue; two-body problems; money; what it might take to get hired (besides luck); data science bootcamps; undergraduate research mentorship; and whatever else you can think to ask about.

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