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Machine Learning Research Manager at Apple
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Technical University of Munich
Doctor of Philosophy - PhD, Electrical Engineering and Computer Science
N/A – Present
Università Politecnica delle Marche
Bachelor of Science (B.Sc.), Electronic Engineering and Computer Science
N/A – Present
Università Politecnica delle Marche
Master of Science (M.Sc.), Electronic Engineering and Computer Science
N/A – Present
Apple
Machine Learning Research Manager
June 1, 2020 – Present
Cupertino, California, United States
Apple
Senior Machine Learning Researcher
October 1, 2018 – June 1, 2020
Cupertino, California, United States
Apple
Machine Learning Researcher
October 1, 2016 – October 1, 2018
Cupertino, California, United States
Universität Passau
Associate Researcher
January 1, 2016 – September 1, 2016
Greater Passau Area
audEERING GmbH
Software Engineering Lead
June 1, 2015 – May 1, 2016
Technische Universität München
Associate Researcher
December 1, 2011 – December 1, 2015
Greater Munich Metropolitan Area
The ASC-Inclusion project
November 1, 2011 – December 1, 2014
An EU-funded research project developing interactive games for children with autism to understand and express emotions through facial expressions, vocal intonation and body gestures.
Cultural Fit Analysis
The candidate's background is heavily focused on Machine Learning Research and Software Engineering, which is a significant deviation from the target role of 'Data Analyst'. While there's a strong technical foundation, the direct relevance to typical data analyst tasks (e.g., SQL, BI tools, specific data visualization) is not explicitly demonstrated. The single personal project description is vague regarding technologies used, making it difficult to assess diversity of experience relevant to data analysis.
Soft Skills & Operational Fit
The candidate's experience as a Machine Learning Research Manager and Software Engineering Lead suggests strong leadership, project management, and potentially team collaboration skills. However, specific data on these soft skills is not provided in the assessment.