Bhargav Avasarala
Data AnalystDirector of ML at Paravision
Paravision
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Director of ML at Paravision
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Graduated from U of Michigan with a masters in EE and a focus in machine learning. I've worked on a variety of machine learning problems in different domains and currently work in the biometric space, developing models around face recognition and antispoofing
University of Michigan
M.S., Electrical Engineering
January 1, 2008 – January 1, 2009
University of Michigan
BS, Electrical Engineering, Mathematics
January 1, 2004 – January 1, 2008
Paravision
Director of ML
November 1, 2017 – Present
Washington English Center
Volunteer
January 1, 2014 – March 1, 2014
Northrop Grumman Corporation
Data Scientist (Data Analytics group)
June 1, 2013 – June 1, 2015
University of Michigan
Research Assistant under Silvio Savarese
May 1, 2009 – December 1, 2009
Ann Arbor, MI
Berkeley Sensor and Actuator Center (BSAC)
Research Assistant under Clark Nguyen
May 1, 2007 – August 1, 2007
Berkeley, CA
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on research and development in ML/Computer Vision, which aligns with innovative and technically driven environments. The volunteer experience suggests a willingness to contribute beyond core responsibilities. However, the target role is 'Data Analyst', which might be a slight mismatch given the candidate's senior ML/Computer Vision background. The breadth of skills is focused on ML/CV rather than general data analysis.
Soft Skills & Operational Fit
The candidate's experience as a 'Director of ML' suggests leadership and project management skills. Volunteer experience indicates community involvement. However, specific soft skills like teamwork, problem-solving, and adaptability are not explicitly detailed in the provided data.