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Principal Applied Scientist at Amazon
I'm fascinated by solving problems through Machine Learning! In the last 20 years, I worked on a variety of ML-related applications including spam & abuse detection, black-box optimization, active learning, controlling explore-exploit using multi-armed bandits, personalized recommendation, time-series analysis, probabilistic programming, and causal inference with focus on effect estimation of continuous treatments. What thrills me is not just deriving ML-based algorithms and implementing prototypes, but building real end-to-end systems including science work, software engineering, team & people management, and interact with customers.
University of Potsdam
PhD, Computer Science
January 1, 2008 – January 1, 2012
Humboldt-Universität zu Berlin
Computer Science
January 1, 2005 – January 1, 2006
QUT (Queensland University of Technology)
Semester Abroad, Machine Learning
January 1, 2004 – January 1, 2004
Technische Universität Chemnitz
Diplom (MSc), Computer Science
January 1, 2000 – January 1, 2005
Amazon
Principal Applied Scientist
October 1, 2021 – Present
Amazon
Senior Machine Learning Scientist
November 1, 2018 – October 1, 2021
Amazon
Manager Machine Learning
December 1, 2015 – October 1, 2018
Amazon
Machine Learning Scientist
July 1, 2013 – December 1, 2015
SoundCloud
Machine Learning Engineer
December 1, 2011 – June 1, 2013
Berlin Metropolitan Area
University of Potsdam
Research Associate
October 1, 2008 – November 1, 2011
Potsdam, Brandenburg, Germany
Max Planck Institute for Informatics
Research Associate
December 1, 2006 – September 1, 2008
Saarbrücken, Germany
Humboldt-Universität zu Berlin
Research Associate
July 1, 2005 – November 1, 2006
Berlin Metropolitan Area
Strato AG
Machine Learning Engineer
July 1, 2005 – November 1, 2011
Berlin, Germany
Cultural Fit Analysis
The candidate's career path shows a strong focus on research and development within large tech companies (Amazon) and academic institutions. While their technical skills are exceptional, the target role of 'Data Analyst' might be a step down from their 'Principal Applied Scientist' and 'Manager Machine Learning' roles, potentially indicating a mismatch in career aspirations or a desire for a different type of challenge. The breadth of their experience across different ML domains (spam filtering, recommendation engines, A/B testing, causal inference) demonstrates adaptability and a willingness to tackle diverse problems. However, the specific 'Data Analyst' role might not fully leverage their principal-level scientific leadership experience.
Soft Skills & Operational Fit
The candidate's extensive experience in leading teams and developing complex systems at Amazon suggests strong problem-solving, project management, and collaboration skills. Their academic background and publication record indicate a strong research-oriented mindset and ability to drive innovation. The descriptions imply a high degree of autonomy and responsibility, fitting a senior operational role.