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Engineering Manager, ML @ Instagram
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Cambridge
Doctor of Philosophy (Ph.D.), Computational Neuroscience
January 1, 2012 – January 1, 2016
Massachusetts Institute of Technology
Bachelor of Science (BS), Computer Science
January 1, 2008 – January 1, 2012
Massachusetts Institute of Technology
Bachelor of Science (BS), Bioengineering and Biomedical Engineering
January 1, 2008 – January 1, 2012
Engineering Manager, ML
July 1, 2021 – Present
Apple
Engineering Manager
September 1, 2018 – July 1, 2021
Apple
Motion Engineer
May 1, 2017 – August 1, 2018
MRC Laboratory of Molecular Biology (LMB)
Researcher, Phd Candidate
August 1, 2012 – December 1, 2013
Greater Cambridge Area
National Institutes of Health
Researcher, PhD Candidate
August 1, 2012 – December 1, 2016
Rest Devices
Software Engineer Intern
August 1, 2011 – August 1, 2012
MIT
Undergraduate Researcher
August 1, 2008 – June 1, 2012
Cultural Fit Analysis
The candidate's background is heavily skewed towards research, machine learning engineering, and engineering management, with a strong focus on health and biomedical applications. While there's significant data analysis experience, the target role of 'Data Analyst' might be a step down from their recent management and ML engineering roles. The breadth of skills is strong in ML/data science, but the direct alignment with a pure Data Analyst role, which often involves more business intelligence and reporting, is moderate. Their experience suggests a preference for deep technical problem-solving and algorithm development rather than typical data analyst tasks.
Soft Skills & Operational Fit
The candidate's experience as an Engineering Manager at Apple and Instagram suggests strong leadership, project management, and team collaboration skills. Their academic research background indicates strong problem-solving and analytical thinking. The descriptions of their roles at Apple highlight data science for performance metrics and data engineering for production pipelines, which aligns well with operational aspects of a Data Analyst role.