Jev Gamper
Staff Decision Scientist, Marketplace at Vinted
Vilnius, Vilnius County, Lithuania
Summary
👤
Senior🎓
Top SchoolJev Gamper is a Staff Decision Scientist with a decade of experience applying machine learning, causal inference and experimentation to marketplace problems, currently shaping Vinted’s measurement and experimentation infrastructure. With a PhD-focused background in ML from Warwick and a history leading an 11-person ML team across Vilnius and Berlin, he blends deep research instincts with product-focused delivery across recommendations, safety, vision and NLP. He has built company-wide frameworks for cumulative impact and OKRs, partnered with Stanford on marketplace interference research, and helped grow Vinted’s evidence-driven culture. Outside product work he has driven research programs and mentorship initiatives—from NeurIPS-winning residency mentees to organising Lithuania’s ML community—reflecting a rare mix of hands-on modeling, team leadership and community building. An avid experimenter in life as well as work, he also pursues eclectic technical interests (recently including CNC machining) that feed his practical curiosity.
11 years of coding experience
3 years of employment as a software developer
Computer Numerically Controlled (CNC) Machinist Technology/CNC Machinist, Computer Numerically Controlled (CNC) Machinist Technology/CNC Machinist at TECHIN - Vilniaus technologijų ir inžinerijos mokymo centrasDoctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of Warwick
Github Skills (52)
tiles9
image-reconstruction9
histopathology9
tensorflow9
openslide9
medical-imaging9
vtk8
classification8
python8
segmentation8
agent-based-modeling8
simulation-framework8
cellular-automata8
simulation8
slide8
Programming languages (4)
Github contributions (5)
jgamper/annotated-papers
Jul 2020 - Jan 2021
Contains all research papers read since the end of July 2020 :+1:
Contributions:27 commits, 10 PRs, 8 pushes in 5 months
computational-pathologyresearch-papersscience-researchmachine-learning
jgamper/intrinsic-dimensionality
Jan 2020 - Jul 2020
Use this package to compute intrinsic dimensionality of your task given a fixed neural network in PYTORCH! :fire:
Contributions:70 commits, 2 PRs, 9 pushes in 6 months
neural-networkpytorchdeep-learning
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