Yaroslav Kopotilov
Verified Expert in Engineering
Data Scientist and Developer
Belgrade, Serbia
Toptal member since April 9, 2020
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.
Portfolio
Experience
Availability
Preferred Environment
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.
Work Experience
Prompt and Software Engineer (via Toptal)
Invisible Technologies Inc
- Developed an internal tool for prompt prototyping at a scale in Python.
- Architected and refined several methods for the evaluation of LLM responses.
- Worked with a variety of closed-source and open-source LLM models.
Senior Data Scientist
Bumbee Labs Ab
- Analyzed visit count computation and suggested an algorithm that reduces the out-of-sample model error by 2x.
- Accelerated historical sample data processing in Python by more than 50x using more efficient functions and just-in-time compilation. Reduced the processing time for one day of sample data from one hour to one minute.
- Built a 24/7 data pipeline that consumed WiFi sample data from multiple installations via Advanced Message Queuing Protocol (AMQP).
Founder | Lead Developer
YAFinData
- 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.
- Managed a remote team of up to five developers. Determined the overall direction of product development.
- Analyzed trading opportunities in the UK electricity markets. Backtested several short-term algorithmic strategies. Estimated PnL and risks, accounting for slippage and market impact.
- Created several 24/7 ETL pipelines that collect, clean, and save data for the UK electricity market. Implemented downstream features that are continuously computed from the data feeds in less than 10 ms.
- Developed CI/CD, a backup raw file storage, a parallel redundancy, and a monitoring system to ensure the data collection functions smoothly 24/7.
Developer | Analyst
TickUp AB
- 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
Vitol
- 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
JPMorgan
- 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)
Credit Suisse
- 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 (Intern)
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.
Experience
Interactive Website
https://datascienceforhire.net/Yet Another XML Parser
https://github.com/mysterious-ben/xmlrecordsTop 1 in Time Series Forecast Competition on Kaggle
https://www.kaggle.com/myster/eda-prophet-winning-solution-3-0It 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 Tools
https://github.com/mysterious-ben/apipeGPT Telegram Bot
https://t.me/ok_gpt_botI contributed as a data scientist (GPT model benchmarking, prompt engineering, and text embeddings), software developer (asynchronous Python code and the OpenAI API), project manager, and mentor to junior data scientists.
Data Science Examples
https://github.com/mysterious-ben/ds-examples/Stranger News
https://stranger.news/The fictional news articles and images are generated daily based on real-world news using the OpenAI GPT model. The readers can influence how the story is told as the news unfolds.
Story-driven Text-based Game
LLMs generate events and possible player choices. The player's decisions determine how the world will change and, eventually, what destiny awaits the kingdom.
Education
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
Skills
Libraries/APIs
Scikit-learn, Pandas, NumPy, Matplotlib, OpenCV, REST APIs, SQLAlchemy, SciPy, Python Asyncio, Dask, PyTorch, TensorFlow, Asyncio, AMQP
Tools
Jupyter, Git, StatsModels, PyCharm, ChatGPT, Amazon Athena, ActiveBatch, MATLAB, Kibana, Plotly, Boto 3, Ansible, GitHub, Bitbucket, Grafana
Languages
Python, SQL, R, C++, Java, HTML, CSS, XML
Storage
Data Pipelines, Oracle SQL, PostgreSQL, Amazon S3 (AWS S3), SQLite, MongoDB, PostGIS
Frameworks
LightGBM, Spark, Flask
Paradigms
Object-oriented Programming (OOP), Quantitative Research, Agile Software Development, Functional Analysis, STOMP
Platforms
Jupyter Notebook, Docker, Linux, MacOS, Amazon Web Services (AWS), Visual Studio Code (VS Code), NVIDIA CUDA, Heroku
Industry Expertise
Project Management
Other
Predictive Modeling, Forecasting, Data Analysis, Predictive Analytics, Data Science, Statisticians, 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, Prompt Engineering, Bayesian Statistics, Stock Market, 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, Applied Physics, Mentorship, Leadership, Technical Leadership, Mentorship & Coaching, Bayesian Inference & Modeling, CTO, Large Language Models (LLMs), ChatGPT Prompts, Coaching, Workshops, WiFi, Market Risk, Software Engineering
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