Matej Rizman
Avera AI at Google
Warsaw, Masovian Voivodeship, Poland
Summary
🤩
Rockstar🎓
Top SchoolMatej Rizman is a seasoned engineering leader and cloud architect with over 15 years of experience in financial services and insurance, currently leading Avera AI at Google. He blends executive experience as a former CIO/CTO with hands-on expertise in cloud (GCP Professional Cloud Architect), distributed systems, ML, big data and cybersecurity, and has managed teams of 30+ people. A mathematician by training (University of Ljubljana) with executive education from Cambridge Judge Business School and an FT Non-Executive Director Diploma, he is equally comfortable shaping strategy and diving into technical details. He has co-authored three successful insurance products, helps build data-driven organizations, and maintains a practical commitment to reliability—evidenced by test infrastructure contributions to the high-performance tf-quant-finance TensorFlow library. An active investor and startup mentor, he brings a rare mix of product, technical and governance experience that accelerates complex digital transformations.
11 years of coding experience
Cambridge Senior Management Programme, Cambridge Senior Management Programme at Cambridge Judge Business SchoolFinancial Times Non-Executive Director Diploma, Financial Times Non-Executive Director Diploma at Financial TimesMaster's degree (equivalent University degree), Master's degree (equivalent University degree) at University of Ljubljana, Faculty of Mathematics and Physics
Github Skills (5)
tensorflow10
python10
test-automation10
testing10
finance9
Programming languages (6)
Github contributions (5)
google/tf-quant-finance
Jul 2019 - Oct 2022
High-performance TensorFlow library for quantitative finance.
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:1 release, 129 commits, 3 PRs in 3 years 3 months
Contributions summary:Matej primarily focused on improving the testing infrastructure of the `tf-quant-finance` library. Their contributions included fixing docstrings in Python tests, modifying imports to use the public Abseil Python library, and correcting import order. The user also removed remnants of internal project naming, autoformatted files, and addressed issues related to loading Sobol data files. Their work directly contributed to the test suite's correctness and maintainability.
tensorflowquantitative-financepythonfinancenumerical-methods
matejr/tf-quant-finance
Sep 2019 - Jan 2020
High-performance library for quantitative finance using TensorFlow
Contributions:14 commits, 2 PRs, 15 pushes in 4 months
tensorflow
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.