Help & Supportcareers@gravityer.com
Machine learning Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Building agents for automation of Metas ranking pipeline
RPTU Kaiserslautern-Landau
Master of Science (M.Sc.), Mathematics
January 1, 2007 – January 1, 2008
The Faculty of Engineering at Lund University
Master of Engineering (M.Eng.), Applied Mathematics
January 1, 2003 – January 1, 2008
Meta
Machine Learning Engineer
May 1, 2025 – Present
Bellevue, Washington, United States · Hybrid
Microsoft
Senior Applied Scientist
July 1, 2023 – May 1, 2025
Microsoft
Senior Data and Applied Scientist
December 1, 2018 – July 1, 2023
Microsoft
Senior Data Scientist - Machine Learning
November 1, 2016 – December 1, 2018
Strossle
Machine Learning Engineer
January 1, 2016 – October 1, 2016
Malmö
Actionbase
Data Scientist
September 1, 2014 – December 1, 2015
Stockholm
Nordea
Quantative Analyst - Stress Test and Simulation Development
August 1, 2013 – September 1, 2014
Greater Stockholm Metropolitan Area
Danske Markets
Desk Quant / FX Option Dealer
March 1, 2011 – March 1, 2013
Danske Markets
Quantitative Analyst
May 1, 2008 – April 1, 2011
Fraunhofer ITWM
Research assistant
March 1, 2007 – August 1, 2007
Fall 2020 MLADS Conference Presenter
CCLAIM Consulting LLC
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on advanced data science, machine learning, and quantitative analysis, primarily within large corporate environments. While the experience is deep in these areas, the target role of 'Data Analyst' might be a step down in terms of technical depth and strategic influence compared to their 'Machine Learning Engineer' or 'Senior Applied Scientist' roles. The breadth of projects across different domains (ranking pipelines, resource optimization, OneNote Copilot, Windows Photo app, news recommendations, financial modeling) indicates adaptability. However, the specific alignment with a typical 'Data Analyst' role, which often involves more dashboarding, reporting, and less advanced model development, is not perfectly clear. The candidate's profile suggests a strong fit for a senior or lead Data Scientist/ML Engineer role, rather than a pure Data Analyst.
Soft Skills & Operational Fit
The candidate's extensive experience in large organizations like Microsoft and Meta suggests strong operational fit, including collaboration within large teams and managing complex projects. The descriptions imply problem-solving and analytical thinking. However, without psychometric test results or interview data, specific soft skills like communication clarity, work attitude, or stress handling cannot be objectively assessed.