Data Scientist2019 - 2020Vitol
Technologies: ActiveBatch, Kibana, AWS Athena, AWS S3, Git, Oracle SQL, Python
- Created market analysis tools and systematic strategies for coal, power, and crude desks. Covered all phases of a data science project, including project set up, data pipelines, modeling, and deployment.
- Worked with small—50 samples and big—several terabytes—of tabular data.
- Contributed individually and in collaboration with the data science and IT team.
- Assisted Vitol’s employees in Python and machine learning training.
Model Validation, Commodities — Associate2017 - 2018JPMorgan
- Implemented from scratch a custom version of the extended Kalman filter to calibrate exotic option pricing models that outperformed the existing calibration methods.
- Reviewed ten pricing models' options and their implementations in commodities and credit.
- Measured and mitigated numerous model risks in collaboration with the desk and developers.
- Mentored junior employees during their review work.
Algorithmic Trading — Intern2016 - 2016Credit Suisse
Technologies: MATLAB, R, SQL, Python
- Designed and implemented two mid-frequency trading strategies for the commodity desk.
- Analyzed portfolio hedging strategies using risk factors for the equity desk.
- Implemented a data pipeline that cleaned and transformed tabular data for the equity desk.
Research — Intern2015 - 2015Novosibirsk State University
Technologies: OpenCV, Python
- Wrote a research paper describing a special metric for images with multiple shapes using Fourier descriptors.
- Implemented a classification algorithm that achieved 98% accuracy on a dataset with 19 classes of images.
- Presented the results at the scientific conference MNSK 2015, Novosibirsk.