Help & Supportcareers@gravityer.com
Machine Learning @ Meta
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
UCL
PhD, Machine Learning
January 1, 2008 – January 1, 2013
UCL
Master of Science, Intelligent Systems / Machine Learning
January 1, 2007 – January 1, 2008
Universität Osnabrück
Bachelor of Science, Cognitive Science
January 1, 2007 – January 1, 2008
Maven
Instructor: Modern Forecasting in Practice
August 1, 2023 – Present
Remote
Sphere
Instructor: Modern Forecasting in Practice
January 1, 2023 – July 1, 2023
Remote
Meta
Software Engineer
November 1, 2022 – Present
Germany
Amazon Web Services (AWS)
Principal Machine Learning Scientist
October 1, 2021 – November 1, 2022
Amazon Web Services (AWS)
Senior Machine Learning Scientist
April 1, 2018 – October 1, 2021
Amazon
Senior Machine Learning Scientist
October 1, 2017 – March 1, 2018
Berlin Metropolitan Area
Amazon
Machine Learning Scientist
July 1, 2013 – September 1, 2017
Berlin Metropolitan Area
Cultural Fit Analysis
The candidate has a strong background in machine learning and data science, which aligns well with roles requiring analytical rigor. Their experience spans large tech companies (Amazon, AWS, Meta) and instructional roles, indicating adaptability and a desire to share knowledge. However, the target role is 'Data Analyst', which might be a step down from their Principal ML Scientist and Software Engineer roles, potentially indicating a mismatch in career trajectory or expectations. The lack of specific 'Data Analyst' roles or projects focused purely on data analysis (rather than ML model development) suggests a potential gap in direct cultural fit for a pure analyst role, despite strong analytical foundations.
Soft Skills & Operational Fit
The candidate's experience as an instructor suggests strong communication and presentation skills. Their long tenure at Amazon/AWS in senior ML roles indicates problem-solving, leadership, and operational experience in a large tech environment. However, specific details on collaboration, stress handling, or work attitude are not available from the provided data.