Yaroslav Kopotilov
Verified Expert in Engineering
Data Scientist and Developer
Belgrade, Serbia
Toptal member since April 9, 2020
Yaroslav is a senior data scientist with extensive experience in business analysis, predictive modeling, data visualization, data orchestration, and deployment. He has a proven track record of managing complex data science projects and leading small, agile developer teams.
Portfolio
Experience
- Python - 8 years
- Machine Learning - 7 years
- Statistics - 5 years
- Time Series Analysis - 5 years
- Data Engineering - 4 years
- SQL - 4 years
- Data Visualization - 3 years
- Stakeholder Engagement - 3 years
Availability
Preferred Environment
Git, Jupyter, Linux, Visual Studio Code (VS Code), SQL, Python, MacOS, NoSQL
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
[Python + Machine Learning] Developer for an AI-powered software engineering platform
codeValet Inc.
- Refactored PyTorch code in a complex async codebase, accelerating AI pipelines by over 50x.
- Debugged and improved several mathematical algorithms, enhancing the reliability of the AI platform.
- Analyzed and recommended improvements to the overall architecture of the AI platform.
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 and AI/ML Engineer
Bumbee Labs Ab
- Designed an improved version of a visit count algorithm that reduces the out-of-sample model error by 50%.
- Developed a framework for robust ML model prototyping and evaluation by the data science team.
- Accelerated historical sample data processing in Python by more than 50x through the use of more efficient functions and just-in-time compilation. This 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 and saved them in an SQL database for historical data analysis and model evaluation.
Lead Data Scientist, AI/ML Engineer and Developer | CEO | Founder
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 and AI Engineer
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
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
Data Sanity Talks
https://datasanity.dev/Cancer Treatment Research
https://www.milner.cam.ac.uk/machinelearning/OpenAI GPT 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.
Stranger News
https://stranger.news/Top 1 in Time Series Forecast Competition on Kaggle
https://www.kaggle.com/myster/eda-prophet-winning-solution-3-0Exploring and visualizing the dataset was both fun and rewarding, as I uncovered interesting quirks in the data. Notably, I soon realized the dataset had been synthetically generated, which provided a crucial clue for solving the problem. In the end, my analysis paid off — my team secured first place!
Interactive Website
https://datascienceforhire.net/Data Science Examples
https://github.com/mysterious-ben/ds-examples/Python Data Pipelining Tools
https://github.com/mysterious-ben/apipePlease check out my GitHub page to see other data science and data engineering packages.
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, SpaCy
Tools
Jupyter, Git, StatsModels, PyCharm, ChatGPT, Algorithm Design, Amazon Athena, ActiveBatch, MATLAB, Kibana, Plotly, Boto 3, Ansible, GitHub, Bitbucket, Grafana, GIS
Languages
Python, SQL, R, C++, Java, HTML, CSS, XML
Storage
Data Pipelines, Oracle SQL, PostgreSQL, Amazon S3 (AWS S3), SQLite, MongoDB, PostGIS, NoSQL
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, Ubuntu
Industry Expertise
Project Management, Trading Systems
Other
Predictive Modeling, Forecasting, Data Analysis, Predictive Analytics, Data Science, Statistics, Machine Learning, Supervised Learning, Algorithmic Trading, Regression, Data Analytics, Backtesting Trading Strategies, Minimum Viable Product (MVP), Feature Engineering, Data Cleansing, 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, Natural Language Processing (NLP), Financial Modeling, Numba, Financial Software, OpenAI, Metrics, Prompt Engineering, Bayesian Statistics, Large Language Models (LLMs), Stock Market, AI Consulting, Data Structures, AI Algorithms, Mathematical Modeling, Monte Carlo, Monte Carlo Simulations, Architecture, Finance APIs, Financial Market Data, Real-time Data, 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, IT Product Management, Trade Finance, Audio Processing, Numerical Methods, Reports, Applied Physics, Mentorship, Leadership, Technical Leadership, Mentorship & Coaching, Bayesian Inference & Modeling, CTO, ChatGPT Prompts, Coaching, Workshops, WiFi, Market Risk, Software Engineering, Open-source LLMs, Retrieval-augmented Generation (RAG), Biotechnology, Investment Banking, Integration, Vector Databases, Geospatial Data, API Integration, AI Chatbots, Chatbots, Product Management, Lean Project Management, Communication, Community, Public Speaking, Hugging Face, Cython
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