Building AI Safety & Security @ Gray Swan
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Amsterdam
Master’s Degree, Artificial Intelligence
January 1, 2014 – January 1, 2018
University of Amsterdam
Bachelor’s Degree, Artificial Intelligence
January 1, 2011 – January 1, 2014
Gray Swan AI
AI Safety Research Engineer
November 1, 2025 – Present
Cambridge AI Safety Hub
AI Safety Research Project (MARS)
July 1, 2025 – September 1, 2025
Cohere
Member of Technical Staff
November 1, 2023 – November 1, 2025
Xebia
Machine Learning Engineer
July 1, 2022 – November 1, 2023
Vattenfall
Lead Data Scientist (via Xebia)
July 1, 2022 – September 1, 2023
Amsterdam, North Holland, Netherlands
NumFOCUS
Co-chair PyData Global
January 1, 2021 – November 1, 2021
Xebia
Data Science Educator
August 1, 2020 – November 1, 2023
NumFOCUS
Co-chair of PyData Amsterdam
December 1, 2018 – October 1, 2024
Aidence
Graduate Thesis (part-time) / Regular Employee (part-time)
August 1, 2016 – August 1, 2017
Aidence
Deep Learning Engineer
August 1, 2016 – July 1, 2020
Aidence
Internship
April 1, 2016 – August 1, 2016
Vrije Universiteit Amsterdam / VU
Teaching Assistant
February 1, 2016 – March 1, 2016
Microsoft
Internship
October 1, 2015 – January 1, 2016
University of Amsterdam
Mentor BSc Information Studies
September 1, 2013 – July 1, 2015
Amsterdam, North Holland, Netherlands
University of Amsterdam
Teaching Assistant BSc Artificial Intelligence
April 1, 2013 – June 1, 2015
Amsterdam, North Holland, Netherlands
Cultural Fit Analysis
The candidate's extensive involvement in PyData communities (Co-chair PyData Global, Co-chair of PyData Amsterdam) indicates a strong commitment to community building, knowledge sharing, and continuous learning, which are positive indicators for cultural fit. The diverse roles from research to education and industry suggest adaptability. However, the target role is 'Data Analyst' while the candidate's experience is heavily skewed towards 'AI/ML Engineer' and 'Data Scientist' roles, which might indicate a mismatch in expectations or a potential overqualification for a pure analyst role. The candidate's experience level (25 years) seems to be an error in the input data, as the career timeline suggests approximately 8-10 years of professional experience since completing their Master's degree.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and educational skills through roles like Lead Data Scientist and Data Science Educator. Involvement in PyData communities suggests a collaborative and community-oriented mindset. The descriptions indicate an ability to drive strategic decision-making and translate complex technical concepts.