Verified Expert in Engineering
Data Scientist and Developer
Yaroslav is a full-stack data scientist with experience in business analysis, predictive modeling, data visualization, data orchestration, and deployment. He leverages a wide range of machine learning methods, statistics, and business insights to find just the right solution for a problem. Above everything else, Yaroslav aims to deliver a project that would be truly useful for his clients.
Git, Jupyter, PyCharm, Linux, Visual Studio Code (VS Code), SQL, Python
The most amazing...
...thing I've developed is an algorithmic trading strategy powered by multiple data pipelines and one ML model running 24/7.
CEO | Lead Developer
- Designed and built a financial data and data analytics platform. The data is shipped in a unified, user-friendly format and can be accessed via a web app and REST API.
- Created several 24/7 ETL pipelines that collect, clean, and upload data in an SQL database. Currently, the data feeds cover the UK electricity market.
- Implemented downstream features that are computed from data feeds in real-time. It takes over 20ms for a feature to update when new data arrives.
- Developed CI/CD, a backup raw file storage, a parallel redundancy, and a monitoring system to ensure the data collection functions smoothly 24/7.
- Determined an overall direction of product development, designed an execution plan, and managed team members.
- Took responsibility for further development of the data platform and management of business operations.
Developer and Analyst
- 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 Scientist
- 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 — Associate
- Implemented a custom version of the extended Kalman filter from scratch 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 — Intern
- 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.
Novosibirsk State University
- 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.
Yet Another XML Parserhttps://github.com/mysterious-ben/xmlrecords
Top 1 in Time Series Forecast Competition on Kagglehttps://www.kaggle.com/myster/eda-prophet-winning-solution-3-0
It was very fun to explore and visualize the dataset, to find interesting quirks in it. In particular, soon it became clear that this data had been synthetically generated, which gave out an important clue on how to solve this problem. And it was very exciting that in the end, my analysis paid off and I scored the first place!
Also, I was working on this project with my ex-colleague, so it was a good collaborative experience with just a touch of project management. Of course, it was far from the complexity of managing a real data science project—still, it gave me at least some sense of what might be waiting ahead.
Python Data Pipelining Toolshttps://github.com/mysterious-ben/apipe
GPT Telegram Bothttps://t.me/ok_gpt_bot
Data Science Exampleshttps://github.com/mysterious-ben/ds-examples/
Python, SQL, R, C++, Java, HTML, CSS, XML
Scikit-learn, Pandas, NumPy, Matplotlib, OpenCV, REST APIs, SQLAlchemy, SciPy, Python Asyncio, Dask, PyTorch, TensorFlow, Asyncio
Jupyter, Git, StatsModels, PyCharm, Amazon Athena, ActiveBatch, MATLAB, Kibana, Plotly, Boto 3, Ansible, GitHub, Bitbucket, Grafana
Data Science, Object-oriented Programming (OOP), Quantitative Research, Agile Software Development, Functional Analysis, STOMP
Data Pipelines, Oracle SQL, Amazon S3 (AWS S3), SQLite, PostgreSQL
Predictive Modeling, Forecasting, Data Analysis, Predictive Analytics, Statistics, Machine Learning, Supervised Learning, Algorithmic Trading, Regression, Data Analytics, Backtesting Trading Strategies, Time Series, Web Dashboards, Artificial Intelligence (AI), Time Series Analysis, Mathematics, Data Visualization, Stakeholder Engagement, Data Engineering, Option Pricing, Unsupervised Learning, Finance, Trading, Financial Data, Dashboards, Quantitative Analysis, Quantitative Finance, Quantitative Risk Analysis, Statistical Analysis, Financial Modeling, Numba, Financial Software, OpenAI, Metrics, Machine Learning Operations (MLOps), Code Deployment, Algorithms, Futures & Options, Energy, Systematic Trading, Deep Learning, Probability Theory, Mathematical Analysis, Applied Mathematics, Derivative Pricing, Chemistry, Stochastic Modeling, Stochastic Differential Equations, Econometrics, Economics, Computer Vision, Software Development, Genetic Algorithms, Dash, Financial Markets, Data Mining, Equity Market Data, Cloud Services, Remote Team Leadership, Technical Hiring, Code Review, IT Project Management, Team Leadership, Quantitative Modeling, Big Data, APIs, OpenAI GPT-3 API, OpenAI GPT-4 API, Telegram Bots, Natural Language Processing (NLP), IT Product Management, Trade Finance, Audio Processing, Numerical Methods, Reports
LightGBM, Spark, Flask
Jupyter Notebook, Docker, Linux, MacOS, Amazon Web Services (AWS), Visual Studio Code (VS Code), NVIDIA CUDA
Master's Degree in Financial Mathematics
Université Pierre et Marie Curie - Paris, France
Master's Degree in Applied Mathematics
École Polytechnique - Paris, France
Master's Degree in Mathematics and Computer Science
Novosibirsk State University - Novosibirsk, Russia
Bachelor's Degree in Probability and Statistics
Novosibirsk State University - Novosibirsk, Russia