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Machine Learning Engineering Manager at Spotify
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced Machine Learning Engineer with a demonstrated history of working in the financial services industry. Bachelor of Science (B.S.E.) in Computer Science from University of Michigan College of Engineering.
University of Michigan College of Engineering
Bachelor of Science (B.S.) in Engineering, Computer Science
January 1, 2010 – January 1, 2014
Spotify
Machine Learning Engineering Manager
October 1, 2022 – Present
Spotify
Senior Machine Learning Engineer
August 1, 2022 – October 1, 2022
Spotify
Machine Learning Engineer
June 1, 2018 – August 1, 2022
Capital One
Machine Learning Engineer
July 1, 2016 – May 1, 2018
Capital One
Software Engineer, Technology Development Program
July 1, 2014 – July 1, 2016
Cultural Fit Analysis
The candidate has a strong background in large, well-known tech companies (Spotify, Capital One), indicating experience in structured environments. The transition from software engineering to machine learning and then management shows adaptability and a drive for growth. The early experience in cybersecurity and big data processing suggests a diverse technical foundation. However, the recent focus on ML might require re-alignment for a pure Big Data Engineer role.
Soft Skills & Operational Fit
The candidate's progression from Software Engineer to Machine Learning Engineering Manager at Spotify suggests strong leadership, problem-solving, and project management skills. Experience in a security operations center indicates analytical and incident response capabilities. However, specific details on collaboration and communication styles are not provided.