Position: Data Scientist / Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 3

- The week I joined a project that has been going on for half a year, I suggested a different approach, and it raised the R2 score from about 0.01 to 0.5 on real-world economic data.
- In a behavior prediction project helped the client to change perspective on the task, metrics and results' evaluation, which led to more insights on the dats and subsequent precision increase (10-20% for the same recall for a late-term project), and more importantly to a change of their perception of our team's success and to years of subsequent collaboration with this client.
- Implemented from scratch several cutting-egde meta-models only with basic libraries for different projetcs, and in non-poc projects they were succesfully industrialized (using only basic libraries was a client's request, I'm not that arrogant)
I have worked in a client-facing role on different projects on:
• Time series forecasting with various underlying models (neural networks, Markov and Bayesian models, standard tools like gradient boosting, linear regression etc).
• Causal inference: establishing an effect of a particular factor (way of contact a client, prices of products) on a desired outcome. In all the projects I identified and implemented the most appropriate models from research papers into shipping products.
• Reinforcement learning: drone flying in a simulation and (a personal project) optimal quantum control.
• I also participated in a non-ML international interdisciplinary research project on quantum-assisted computation. I developed architecture and a compiler for a quantum co-processor and evaluated potential computational benefits of the device.
- relocation to US/Canada (або до України: краще щось робити там, ніж сидіти тут в ЄС ніби як осторонь)
- diverse projects
- collaborative team