[Please Note: This session has already occurred. Go to the News Story to read about what happened.]
Interested in a statistics or data science position in the hi-tech industry sector? Then this session should interest you!
This virtual career fair event is the eleventh in a series of Virtual Career Fairs that NISS has been hosting. (Check out earlier virtual career fair sessions!)
Some of these sessions have focused on academic positions, others on positions in government agencies and industry. This session describes opportunities for statisticians/data scientists from three companies. Senior statisticians from Facebook, Netflix, and Google will provide attendees with an inside look at the research that statisticians in these companies get involved in and career opportunities for you to consider!
Speakers for this session include:
Amir Najmi - Principal Data Scientist at Google
Martin Tingley - Head of the Experimentation Platform Analysis Team Lead at Netflix
Elliott Merriam - Research Data Scientist at Facebook
This session will be moderated by Piaomu Liu (Bentley University)
Each presenter will have 15 minutes to address the following general topics:
- What are the job opportunities for statisticians/data scientists/analysts in your company?
- Describe the range of skills statisticians/data scientists/analysts need to succeed in your company?
- What is the career path for statisticians/data scientists/analysts in your company?
- Is your firm currently hiring statisticians/data scientists/analysts?
- What advice would you give to students based on your experience?
Please use your .edu, .gov or .com email address when registering. The Career Fair will be conducted using Zoom.
About the Speakers
Amir Najmi, Principal Data Scientist, has worked at Google for 16 years, the last six at Google San Francisco helping Google make better product decisions through cross-product data analysis. For the decade before that, Amir worked in Search Ads Quality where he also led the data science team. His technical interests include large scale experimentation, prediction, causal inference, the role of human insight in machine learning and in "quality". Editor of the Data Science blog, he has been very involved in hiring for and developing the Data Science ladder at Google over the last few years. He has a PhD from Stanford University where he studied information theory and statistics.
Martin Tingley leads a multidisciplinary team on the Netflix Experimentation Platform, focused on developing and scaling both statistical methodology and software solutions to improve decision-making across the company. Prior to joining Netflix in 2017, Martin spent several years modeling and pricing catastrophe risk at Insurance Australia Group. In an earlier academic career, Martin was an Assistant Professor in Statistics and Meteorology at Penn State University. Martin holds a Ph.D. in Earth and Planetary Sciences and an M.A. in Statistics from Harvard University, and a B.Sc. in Physics from the University of Toronto.
Elliott Merriam obtained a Ph.D in Neuroscience at the University of Wisconsin-Madison in the lab of Dr. Erik Dent, where he studied the effects of neural activity and synaptic communication on molecular dynamics in living brain cells using real-time fluorescence microscopy. After the Ph.D., Elliott was a Senior Fellow at the University of Washington in the lab of Dr. Larry Zweifel, where he studied the neural circuitry underlying motivated behaviors in mice. Following his postdoctoral fellowship, and before transitioning into Data Science, Elliott joined the patent practice of law firm Wilson Sonsini Goodrich & Rosati, where he worked on patent applications and litigation matters. To pursue a career in Data Science, Elliott accepted a fellowship in the Insight Data Science program, which led to a role as Data Scientist for iSpot.tv, a television advertising analytics company. After iSpot, Elliott joined Facebook, where he has worked as a Data Scientist on integrity and security problems for the past 4 years.