Senior Data Scientist (Independent Full-time Consultant)
2020 - 2021TickUp- Led the alpha research project focused on getting trading signals based on daily credit card usage data in the US, starting from communication with the vendors and data evaluation to model building, backtesting, and running the production pipeline.
- Built prediction models of the company's revenue. Assembled the linear models, decision tree methods, ensembles, revenue surprise, and market reactions based on the analysis of consumer spending trends for more than 250 public companies.
- Developed the time series prediction models of daily consumer spending for more than 400 companies, including Prophet, SARIMAX, and state space models.
- Gained experience with data providers including, Bloomberg, Refinitiv, Estimize, ConsumerEdge, Algoseek, Ravenpack, Apptopia, and Quandl.
- Coordinated the data acquisition and data usage to provide consistency and point in the timeliness of backtesting procedures.
Technologies: Python 3, Data Science, Quantitative Research, Time Series Analysis, Pandas, Scikit-learn, StatsModels, PostgreSQL, ClickHouseData Scientist
2018 - 2019Quoine- Built an adaptive market-making strategy for liquid crypto markets, which included risk control, fair price estimation and prediction of bid-ask spread related market metrics.
- Adjusted a Kalman filter model for FX rates in multi-market executions.
- Designed and developed a flexible backtesting framework for testing and optimization of high-frequency trading strategies; developed effective visual reports of strategy performance.
- Optimized an ETL pipeline and reporting system for analysis of trading activity on different external exchanges, redesigned daily and monthly auto-generated P&L reports.
- Performed research and prototyping for improving predictions of various market metrics (Linear models, decision tree methods, GARCH, recurrent neural networks).
- Led the project to support internal and external audit requests: ad-hoc analysis, reporting and data investigations, data issues backtracking and coordination of required fixes.
Technologies: Git, Bash, PostgreSQL, SQL, IPython, Bokeh, Keras, Scikit-learn, SciPy, Pandas, PythonData Analyst (Contractor)
2017 - 2017Soft Retail- Identified fraud cases in transaction and customer data using unsupervised anomaly detection algorithms (local outlier factor, and isolation forest).
- Designed a database scheme and implemented a regular transfer of client data from local CRM to relational DB (PostgreSQL).
- Developed a set of effective indices and indicators for analysis and visualization of profit trends, customer segments, and customer behavior trends.
- Implemented and deployed an interactive online dashboard to track main performance indices.
Technologies: Git, IPython, PostgreSQL, Scikit-learn, Bokeh, Pandas, PythonQuantitative Analyst
2009 - 2015Applied Technologies- Developed a set of metrics for investor competence rankings based on SEC13F filings.
- Applied data mining techniques (visualization, decision trees, and clustering) to identify a group of stocks and main trading patterns useful for the generation of buy/sell signals.
- Developed and backtested a set of index strategies; each strategy aimed to cover a specific decision logic, for example, build a balanced portfolio based on top competent investors and so on.
Technologies: MATLAB, Statistics, Microsoft Excel, SQL, JavaLecturer Assistant
2007 - 2010Chelyabinsk State University- Organized practical and laboratory classes (including econometrics, probability theory and statistics, and Monte-Carlo techniques).
- Contributed to a few research projects devoted to statistics and mathematical modeling.
- Developed study materials and home projects for the course "Applied Probability Theory and Monte-Carlo."
Technologies: MATLAB, Fortran, Java