
Sr. Data Scientist, Microsoft
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of New Haven
Master’s Degree, Data Science
January 1, 2016 – January 1, 2017
UC Santa Barbara
PhD, Biomolecular Science and Engineering
January 1, 2003 – January 1, 2010
The Ohio State University
B.S., M.S., Materials Science and Engineering
January 1, 1997 – January 1, 2003
Microsoft
Senior Data Scientist
March 1, 2026 – Present
Redmond, Washington, United States
Mars
Sr. Data Scientist
June 1, 2022 – January 1, 2026
New Relic, Inc.
Senior Software Engineer/ML
August 1, 2017 – May 1, 2022
San Francisco Bay Area
Silicon Valley Bank
Data Scientist
March 1, 2017 – August 1, 2017
San Francisco Bay Area
MycoWorks
Scientific Project Manager (Contractor)
July 1, 2016 – December 1, 2016
San Francisco Bay Area
Stanford University
Post-Doc, Endy Lab, Dept. of Bioengineering
March 1, 2014 – June 1, 2016
Stanford, CA
National Institute of Standards and Technology
NRC Post-Doc, Genome Scale Measurements Group, Biosystems and Biomaterials Division
March 1, 2014 – March 1, 2016
Stanford, CA
National University of Singapore
Visiting Academic Fellow
January 1, 2014 – February 1, 2014
College of Alice and Peter Tan, NUS, Singapore
University of Leeds
Post Doctoral Research Fellow
November 1, 2010 – November 1, 2013
Imperial College London
Visiting Scientist
November 1, 2010 – June 1, 2011
London, United Kingdom
Engineers Without Borders
Volunteer
January 1, 2004 – January 1, 2010
UCSB
PhD student
January 1, 2003 – January 1, 2010
The Ohio State University
Masters Research
January 1, 2002 – January 1, 2004
Columbus, Ohio
Cultural Fit Analysis
The candidate's diverse background, including academic research, volunteer work with Engineers Without Borders, and roles in various industries (biotech, finance, tech), suggests a broad perspective and adaptability. The long academic career followed by a pivot into data science indicates a strong drive for learning and applying knowledge to new challenges. However, the target role is 'Data Analyst,' while the candidate's recent experience is primarily 'Senior Data Scientist' and 'Senior Software Engineer/ML.' This might indicate a potential mismatch in the expected scope and depth of responsibilities for a typical Data Analyst role, which often focuses more on reporting and dashboarding rather than advanced modeling or engineering. The lack of specific project details makes it difficult to assess alignment with a collaborative, agile environment.
Soft Skills & Operational Fit
The candidate's resume indicates experience in project management, mentoring, and leading teams (e.g., Engineers Without Borders, University of Leeds). These experiences suggest strong leadership, collaboration, and communication skills. The transition from academic research to industry roles in data science and ML also implies adaptability and a continuous learning mindset. However, without specific psychometric test results, a definitive assessment of operational fit is limited.