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Sr Applied Scientist @ Uber
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
I am highly analytical, a systems thinker, not afraid to be critical, enthusiastic, a problem solver, eager to learn, fascinated by emerging technologies and often - correctly - accused of being a massive geek.
University of Amsterdam
Master of Science (M.Sc.), Information Studies: Human Centered Multimedia
January 1, 2015 – January 1, 2017
University of Groningen
Bachelor of Science (B.Sc.), Information Sciences / Computational Linguistics
January 1, 2010 – January 1, 2014
Zernike College
VWO+, Natuur & Techniek + Natuur & Gezondheid
January 1, 2002 – January 1, 2009
Uber
Sr Applied Scientist
February 1, 2025 – Present
Amsterdam, North Holland, Netherlands · Hybrid
Royal FloraHolland
Data Scientist
June 1, 2021 – February 1, 2025
Aalsmeer, North Holland, Netherlands · Hybrid
DTACT
Data Scientist
April 1, 2018 – June 1, 2021
DTACT
Research Scientist, Machine Learning and Intelligence
April 1, 2017 – April 1, 2018
Rijksuniversiteit Groningen
Student-assistant Center for Information Technology (CIT)
January 1, 2012 – January 1, 2015
Netherlands
Getting Started with AWS Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked in diverse environments, from a large marketplace (Royal FloraHolland) to a cyber security solutions company (DTACT) and academic institutions. This suggests adaptability to different organizational cultures and problem domains. The progression from Research Scientist to Data Scientist and Sr Applied Scientist indicates a growth mindset and ambition. However, the lack of explicit project details or team collaboration descriptions makes a deep cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate's experience descriptions suggest a focus on problem-solving and delivering practical ML solutions. The mention of 'software engineering best practices' indicates an understanding of operational requirements for ML systems. However, without specific psychometric test results or interview data, it is difficult to assess soft skills like teamwork, communication, or stress handling.