
Machine Learning at LinkedIn
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Keywords in reverse chronological order: Spark/Scala, REST APIs, Time series forecasting, Learning to rank, Semidefinite programming, Quantum chemistry
University of Chicago
Doctor of Philosophy (Ph.D.), Physical Chemistry (Theory/Computation)
January 1, 2010 – January 1, 2015
University of Chicago
Master of Science (MS), Physical Sciences
January 1, 2009 – January 1, 2010
Indian Institute of Technology, Bombay
Integrated M. Sc., Chemistry
January 1, 2004 – January 1, 2009
Staff Software Engineer - Machine Learning
April 1, 2017 – Present
Expedia, Inc.
Data Scientist II
January 1, 2016 – March 1, 2017
Greater Chicago Area
Orbitz Worldwide
Software Engineer II - Machine Learning
May 1, 2015 – December 1, 2015
Greater Chicago Area
The University of Chicago
Graduate Researcher
July 1, 2010 – March 1, 2015
Greater Chicago Area
Indian Institute of Technology, Bombay
Undergraduate Research Assistant
May 1, 2008 – May 1, 2009
Mumbai Area, India
Introduction to Data Science
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in research and development, transitioning into industry roles focused on machine learning and data science. While the target role is 'Data Analyst', the candidate's experience is heavily skewed towards 'Data Scientist' and 'Machine Learning Engineer' roles, which typically involve more advanced modeling and less pure reporting/dashboarding. This might indicate a potential mismatch if the Data Analyst role is primarily focused on basic data extraction and visualization. However, the candidate's diverse project experience across different companies (LinkedIn, Expedia, Orbitz) and academic research demonstrates adaptability and a broad interest in data-driven problem-solving.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership in projects and presenting results to senior management, suggesting strong communication and stakeholder management skills. The academic background implies strong analytical rigor and independent research capabilities. The transition from research to industry roles indicates adaptability and a results-oriented mindset.