
ML Research Engineer
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine learning engineer with experience in healthcare and financial news. Skilled in dataset construction, deep learning and model deployment. Strong analytical foundation with graduate degree in physics.
Rutgers University
Doctor of Philosophy (Ph.D.), Condensed Matter Physics
January 1, 2007 – January 1, 2012
UC San Diego
Doctor of Philosophy (Ph.D.), Condensed Matter Physics
January 1, 2006 – January 1, 2007
Caltech
Bachelor of Science (B.S.), Physics
January 1, 2001 – January 1, 2005
Hawkfish LLC
Data Librarian
January 1, 2020 – December 1, 2020
New York, United States
Bloomberg LP
ML Research Engineer
February 1, 2019 – November 1, 2023
New York, New York
Insight Data Science
Technical Advisor
February 1, 2018 – August 1, 2022
Greater New York City Area
Imagen Technologies
Machine Learning Research Engineer
November 1, 2017 – December 1, 2018
New York, New York
Insight Data Science
AI Fellow
July 1, 2017 – October 1, 2017
Greater New York City Area
Rutgers University
Postdoctoral Researcher
September 1, 2014 – July 1, 2017
Kavli Institute for Theoretical Physics
Postdoctoral Researcher
September 1, 2012 – July 1, 2014
UC Santa Barbara
Goldman Sachs
Analyst
July 1, 2005 – September 1, 2006
New York, NY
Cultural Fit Analysis
The candidate has a diverse background spanning academia, finance (Goldman Sachs), and various tech companies focused on ML/AI. While the experience is strong in data science and machine learning, the direct alignment with a 'Backend Engineer' role is not explicitly clear from the descriptions, which focus more on data, models, and research rather than core backend system development, APIs, or infrastructure. The breadth of experience suggests adaptability, but the specific fit for a traditional backend role might require further investigation into their software engineering practices.
Soft Skills & Operational Fit
The candidate's experience as a Technical Advisor at Insight Data Science and supervising graduate students suggests strong mentorship and communication skills. Their role as a Data Librarian building cross-team processes indicates organizational and collaborative abilities. The academic background implies strong research and independent problem-solving capabilities.