I am a data science leader interested in shaping up data science teams and organizations that integrate the best features of academia and industry. From academia, the freedom to pursue the most challenging problems, and from industry, the focus on a shared mission, and ability to foster deep collaborations - the commitment to transform science into meaningful impact.
My technical experience ranges from research and discovery of exoplanets using statistical methods; computer vision in medical imaging and remote sensing; application of Bayesian statistics to super-resolve climate model outputs; to scaling and applying machine learning at Vinted. My research results have been peer reviewed and accepted at top ML/AI venues, as well as licensed by multinational Pharmaceutical companies.
I have advised Bsc and Msc projects at Warwick University, as well as mentored research residents at a climate intelligence company. Am a mentor at Women Go Tech, as well as advising a Bsc project at Vilnius University, and an Msc project at ISM. Previously taught at graduate and undergraduate level: Computational Biology; Statistics; Machine Learning.
Currently, I am focused on empowering everyone at Vinted with scientific method. My role involves leadership across all aspects of experimentation and causal inference. From implementing scientific models underlying the experimentation system to setting up technical roadmap and establishing experimentation culture.
Data Science
Operations Research
Machine Learning
Statistics
Data Science