Algorithmic Trading — Principal Researcher and Developer2021 - PRESENTSelf-employed
Technologies: Python, SQL, PostgreSQL, Cloud Services, Docker, Ansible, Git, GitHub, Machine Learning, Data Science, Time Series Analysis, Remote Team Leadership, Technical Hiring, STOMP, Jupyter Notebook, Code Review, IT Project Management, Team Leadership, Quantitative Risk Analysis, Grafana, Data Engineering, Data Analysis, Financial Data, Regression, Statistical Analysis, Algorithms, APIs, Forecasting, Data Analytics
- Onboarded dozens of data sources from files, REST APIs, and messaging protocols to a PostgreSQL database. Configured data transformations in the database to create and update features in real time.
- Configured monitoring and alerting systems for data injection using Python and Grafana.
- Analyzed the price and industry data to generate a signal for a high-frequency algorithmic trading strategy.
- Optimized the strategy to maximize P&L while keeping the default risk minimal. Analyzed the L2 price data to estimate the market impact.
- Managed a team of three developers and handled the overall project management.
Developer and Analyst for a Quantitative Research Project2020 - 2021TickUp AB
Technologies: Algorithms, Python, Statistics, Trading, Financial Markets, Data Mining, Algorithmic Trading, Time Series Analysis, Equity Market Data, Docker, Jupyter Notebook, Data Visualization, Financial Data, Code Review, SQL, Git, GitHub, Data Analysis, Regression, Statistical Analysis, Data Science, Forecasting, Data Analytics
- Analyzed and unified multiple datasets for US equity markets.
- Developed an ML model and several data pipelines of an algorithmic trading strategy.
- Wrote and reviewed both research notebooks and production code.
- Organized a seven-day company meetup, which helped boost team productivity and collaboration.
Energy Trading — Data Scientist2019 - 2020Vitol
Technologies: ActiveBatch, Kibana, Amazon Athena, Amazon S3 (AWS S3), Git, Oracle SQL, Python, Time Series Analysis, Machine Learning, Data Science, Software Development, Data Engineering, Jupyter Notebook, Pandas, Algorithmic Trading, Data Visualization, Bitbucket, Dashboards, Amazon Web Services (AWS), Dash, Web Dashboards, Big Data, Data Analysis, Financial Data, Regression, Statistical Analysis, Forecasting, Data Analytics
- Created market analysis tools and systematic strategies for coal, power, and crude desks. Covered all phases of a data science project, including project setup, data pipelines, modeling, and deployment.
- Analyzed the firm-wide trading market impact under different execution styles.
- Worked with both small (50 data points) and large (several terabytes) datasets.
- Contributed individually and in collaboration with the data science and IT teams.
- Assisted Vitol's employees in Python and machine learning training.
Model Validation, Commodities — Associate2017 - 2018JPMorgan
Technologies: Python, Derivative Pricing, Stochastic Modeling, Time Series Analysis, Machine Learning, Quantitative Analysis, Quantitative Modeling, Quantitative Finance, Quantitative Risk Analysis, Data Analysis, Financial Data, Forecasting, Data Analytics
- 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, Machine Learning, Time Series Analysis, Data Analysis, Financial Data, Regression, Statistical Analysis, Data Science, Forecasting, Data Analytics
- 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, Computer Vision, Mathematics, Machine Learning, Jupyter Notebook, Data Analysis
- Wrote a research paper describing a metric that uses Fourier descriptors to compare shapes with internal gaps.
- 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.