
Research Engineer at Google DeepMind
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I am an Applied Mathematics Ph.D. developing and deploying machine learning solutions on Google's cloud. My interests include state/parameter estimation for stochastic processes, and reinforcement learning.
University of Arizona
Doctor of Philosophy (Ph.D.), Computational and Applied Mathematics
January 1, 2011 – January 1, 2016
University at Buffalo
Bachelor of Science (BS), Mathematics and Computer Science
January 1, 2007 – January 1, 2011
Google DeepMind
Research Engineer
May 1, 2025 – Present
San Francisco Bay Area · Hybrid
Software Engineer
October 1, 2021 – May 1, 2025
Machine Learning Deployment Engineer
August 1, 2017 – March 1, 2022
SendGrid
Big Data Intern
June 1, 2014 – August 1, 2014
GTEAMS
GK-12 Mathematics Teacher
August 1, 2013 – May 1, 2014
Flowing Wells High School
The University of Arizona
Applied Mathematics Ph.D. Student
August 1, 2011 – May 1, 2017
URGE to Compute
Undergraduate Researcher
January 1, 2010 – May 1, 2011
University at Buffalo
Cultural Fit Analysis
The candidate has a strong background in research and development within large, innovative organizations like Google and Google DeepMind. Their academic pursuits and early research roles demonstrate a drive for continuous learning and problem-solving. The transition from a research-heavy background to practical ML deployment and product development indicates adaptability. However, the target role is 'Data Analyst', which might be a step down from their 'Research Engineer' and 'Software Engineer' roles focusing on ML product development. While their skills are highly relevant, the specific alignment with a pure 'Data Analyst' role, which often involves more reporting and dashboarding than advanced ML model development, needs further clarification. The lack of explicit project details makes it difficult to assess diversity beyond their core ML/mathematics focus.
Soft Skills & Operational Fit
The candidate's experience as a GK-12 Mathematics Teacher and Undergraduate Researcher (resulting in publications and presentations) suggests strong communication and collaboration skills. Their work at Google in client-facing roles (ML Deployment Engineer) further supports operational fit in a team-oriented environment. The psychometric test results are not provided, so a full assessment of logical reasoning, work attitude, stress handling, and team collaboration cannot be made.