Linda Hellborg is a Data Scientist with 19 years of cross-disciplinary experience, evolving from molecular biology and evolutionary genetics into web development and applied AI at scale. Currently at IKEA, she builds data-driven solutions and Gen AI software informed by a strong foundation in statistical R analyses, machine learning, and production-focused tooling. Past roles include leading discovery projects at Syngenta where she translated complex breeding data into practical workflows and interactive Shiny apps, and driving bank-wide AI and predictive analytics at Resurs Bank. She pairs domain-depth in biology and genetics with hands-on engineering—having rebuilt front-end projects in React and completed a senior web developer nanodegree—so she comfortably bridges research, product and production. Notably, her career shows a pattern of turning messy, high-volume scientific and business data into actionable systems that improve decision-making and operational outcomes.
19 years of coding experience
7 years of employment as a software developer
Nanodegree, Senior Web Developer, Nanodegree, Senior Web Developer at Udacity
Machine Learning Scientist with Python, machine learning techniques, Machine Learning Scientist with Python, machine learning techniques at DataCamp
Data driven organization, Data driven organization at SAS institute
Doctor of Philosophy (Ph.D.), Evolutionary and population genetics, PhD, Doctor of Philosophy (Ph.D.), Evolutionary and population genetics, PhD at Uppsala University
Master's Degree, Molecular Biology, Msc science, Master's Degree, Molecular Biology, Msc science at Lund University
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