Oskar Lilja
Data AnalystMachine Learning Engineer på Volumental
Volumental
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer på Volumental
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Chalmers University of Technology
Master of Science (M.Sc.), Complex Adaptive Systems
January 1, 2014 – January 1, 2016
Technical University of Munich
Master of Science (M.Sc.), Complex Adaptive Systems
January 1, 2014 – January 1, 2015
Uppsala University
Litteraturvetenskap A
January 1, 2011 – January 1, 2011
Chalmers University of Technology
Bachelor of Science (B.Sc.), Engineering Physics
January 1, 2011 – January 1, 2014
Fyrisskolan
Gymnasieexamen, Naturvetenskaplig inriktning
January 1, 2005 – January 1, 2008
Volumental
Machine Learning Engineer
January 1, 2019 – Present
Greater Stockholm Metropolitan Area
Watty
Machine Learning Engineer
November 1, 2016 – January 1, 2019
Greater Stockholm Metropolitan Area
Ericsson
Machine Learning Intern
June 1, 2016 – September 1, 2016
Göteborg
Division of Mathematical Statistics - Chalmers University of Technology
Master's Thesis: Clustering Cancer Tumours Using Unsupervised Deep Learning Techniques
January 1, 2016 – June 1, 2016
Gothenburg
Sweden Connectivity AB
Software Engineer Intern
July 1, 2014 – August 1, 2014
Greater Stockholm Metropolitan Area
Chalmers University of Technology
Project Assistant
June 1, 2014 – June 1, 2014
Greater Gothenburg Metropolitan Area
Kafé Caffe and HMSHost
Barista
August 1, 2008 – December 1, 2010
Oslo and Arlanda
Cultural Fit Analysis
The candidate has a strong academic background and experience in research-oriented and startup environments (Volumental, Watty). The transition from Machine Learning Engineer to a Data Analyst role suggests a potential alignment with data-driven decision-making, but the specific motivations for this role change are not provided. The diversity of projects, while technically strong, leans heavily towards ML engineering rather than pure data analysis, which might require an adjustment in focus. The lack of explicit project details makes it difficult to fully assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's resume highlights roles requiring analytical thinking and problem-solving. The Master's thesis and internship descriptions suggest an ability to work on complex technical problems independently and within a research context. However, specific soft skills like teamwork, leadership, or communication in a business context are not explicitly detailed in the provided experience descriptions.