Darina Goldin is an engineering team lead and data scientist with ~8–10 years of industry experience bridging applied mathematics, control theory and Python engineering to build robust ETL pipelines, automated model training, and production ML systems. She holds a PhD in Control Science and brings rare rigor from academic proofs into pragmatic solutions, with a particular knack for debugging and modernizing legacy codebases. Darina has led and mentored data science teams across esports, analytics and product companies—often staying hands-on with 50–80% coding time while scaling practices and frameworks. An accredited expert in data science and machine learning, she combines technical leadership with stakeholder communication and a track record of shipping large-scale projects like record linkage and image-recognition systems. Based in Berlin, she speaks multiple languages and has experience across international environments, from academic research to product-driven startups.
8 years of coding experience
13 years of employment as a software developer
Japanese language, Japanese language at Naganuma School of Japanese Language
Erasmus, Erasmus at Universita degli Studi La Sapienza, Rome
Doctor of Philosophy (PhD) Control Science, Doctor of Philosophy (PhD) Control Science at Technische Universität Berlin
Vordiplom Mechanical Engineering, Vordiplom Mechanical Engineering at Technische Universität Braunschweig
An implementation of the Glicko-2 rating system for Python
Contributions:5 pushes, 4 branches in 2 years 11 months
glickopythonrating-systemglicko-2rating
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