
Senior Applied Scientist at Microsoft
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Assessing your cultural and operational fit
Software Engineer with experience in Machine Learning and AI systems for automotive and cloud.
Georgia Institute of Technology
Master of Science - MS, Computer Science
January 1, 2018 – January 1, 2019
University of California, Berkeley
Bachelor of Science (B.S.), Electrical Engineering and Computer Science
January 1, 2010 – January 1, 2014
Microsoft
Senior Applied Scientist - Frontier Tuning Research
May 1, 2026 – Present
Microsoft
Senior Applied Scientist - M365 Cloud Platform
August 1, 2022 – May 1, 2026
Microsoft
Software Engineer II
August 1, 2021 – September 1, 2022
Microsoft
Software Engineer
August 1, 2020 – July 1, 2021
Georgia Institute of Technology
Graduate Teaching Assistant
August 1, 2019 – December 1, 2019
Greater Atlanta Area
Ford Motor Company
Machine Learning Engineer
October 1, 2016 – July 1, 2018
Ford Motor Company
Data Scientist
January 1, 2016 – September 1, 2016
Ford Motor Company
Electrical Systems Engineer - F150
March 1, 2015 – January 1, 2016
Ford Motor Company
Active Safety Engineer
August 1, 2014 – March 1, 2015
Banco Sabadell
Project Finance Summer Intern
June 1, 2013 – July 1, 2013
Greater New York City Area
Banco Sabadell
Project Finance Summer Intern
June 1, 2009 – July 1, 2010
Miami/Fort Lauderdale Area
Cultural Fit Analysis
The candidate has a strong background in large corporate environments (Microsoft, Ford) and academic institutions (UC Berkeley, Georgia Tech). Their diverse project experience, ranging from automotive to cloud platforms and M365 applications, demonstrates adaptability and a broad interest in applying ML/AI across various domains. The transition from Electrical Systems Engineer to Data Scientist/ML Engineer shows a proactive approach to skill development. While the target role is 'Data Analyst', the candidate's experience is significantly more advanced, focusing on Applied Scientist and ML Engineering roles. This might indicate a potential mismatch in the scope of work or expectations for a typical Data Analyst role, which often involves more reporting and dashboarding rather than model development and deployment. However, their foundational data analysis skills are strong.
Soft Skills & Operational Fit
The candidate's experience as a Technical Lead and Graduate Teaching Assistant suggests strong leadership, mentorship, and communication skills. Their work on A/B experimentation, cost reduction, and responsible AI principles indicates a focus on practical, impact-driven solutions and ethical considerations. The rotational program experience at Microsoft demonstrates adaptability and a broad understanding of different problem domains. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.