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Senior Data Scientist at KONUX
I have an undergraduate degree in physics, followed by a Masters in computer science. I then worked for a few years in machine learning and deep learning consulting. I decided I wanted to learn more about the fundamentals of data science, so I pursued a PhD in statistics. In my PhD, I researched efficient Bayesian methods. I made extensive use of Python, especially the JAX package, as well as Tensorflow, to exploit GPUs and automatic differentiation. I am a fan of Bayesian methods, as they are often interpretable, reliable and can incorporate domain expertise, but I also believe in using the right tool for the right job, and sometimes that's a random forest or a neural net. I am excited to apply my knowledge to solve practical problems.
University of Melbourne
PhD, Science
February 1, 2018 – October 1, 2021
Imperial College London
Master of Science (MSc), Computing Science
January 1, 2014 – January 1, 2015
University of Cambridge
Bachelor of Arts (B.A.), Natural Sciences (Physical)
January 1, 2011 – January 1, 2014
Peutinger-Gymnasium Augsburg
Abitur, Physics, Maths, History, English
January 1, 2001 – January 1, 2010
KONUX
Senior Data Scientist
May 1, 2023 – Present
Munich, Bavaria, Germany
KONUX
Data Scientist
March 1, 2022 – May 1, 2023
Munich, Bavaria, Germany
Silverpond Pty Ltd
Machine Learning Engineer
August 1, 2016 – November 1, 2019
Melbourne, Australia
Stratagem Technologies
Quantitative Researcher
October 1, 2015 – May 1, 2016
London, Großbritannien
SPI Lasers
Intern
April 1, 2011 – September 1, 2013
Southampton
The Intelligent Tennis Court
April 1, 2015 – Present
Real-time ball and player tracking engine for tennis on affordable hardware.
Cultural Fit Analysis
The candidate has a strong academic background and professional experience in data science and machine learning, which aligns with a data-driven culture. The project 'The Intelligent Tennis Court' demonstrates personal initiative and passion for applying technical skills. However, the target role is 'Data Analyst', which might be a slight mismatch given the candidate's senior Data Scientist/Machine Learning Engineer experience, potentially indicating overqualification or a desire for a different type of challenge. The breadth of projects is limited to one personal project description.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight problem-solving, independent research, and client interaction, suggesting good operational fit for roles requiring analytical rigor and project ownership. However, specific soft skill assessments are not available.