Top e-commerce retailer in Russia. > Facilitated the development of realtime operational analytics as a core member of the main team within this domain in the company.> Implemented over 10 tools to support real-time logistics operations for several thousand internal employees, primarily focusing on transportation and sorting monitoring.>> Created ETL pipelines for integrating Kafka topics and data from various APIs into the team's database, performing in-database calculations.>> Deployed comprehensive dashboards for operational use.Stack: Python, SQL (Clickhouse), Airflow, Kafka, Rest API, gRPC, Grafana, Superset, Git, JIRA, Confluence.

One of the largest (in top 3) asset-management companies in Russia (AUM 10+ USD BN).> Led the development of a ClickHouse BI database from scratch, creating a suite of BI tools for trading, reporting, and analytics.> Designed and maintained ETL pipelines to seamlessly load data into the ClickHouse database from a variety of sources.> Developed a diverse range of tools that are actively used for:>> Past-performance analytics: Evaluating yield contributions of each asset in the portfolio over time.>> Real-time analytics and trading:>>> Developed a relative value model to calculate bond fair prices by comparing bond prices to their peer rating groups and accounting for liquidity. This model's output is utilized for trading strategies, including the automated trading of over 1,000 small retail portfolios.>>> Created a BI instrument to visualize current asset distribution, market offers, prices, and their comparison with fair prices.>>> Future performance forecasting: Projecting portfolio performance for customizable scenarios and providing alerts on corporate actions of instruments.Stack: Python, SQL (ClickHouse), Airflow, Rest API, Power BI, Grafana, Git, JIRA, Confluence.

Top digital bank in Russia.Developed AML (anti-money laundering) risk management tools from scratch for Tinkoff Broker clients:> Conducted data research to define a comprehensive list of features useful for AML risk analysis.Segmented all clients using cluster analysis on customer transactional and static data, identifying risk zones.> Developed automatic rules to detect and block or flag suspicious new operations, achieving over 80% efficiency.> Created dashboards for monitoring anomalies in risk zones, such as money flows in/out of broker accounts, trades, and depositary transfers.> Established dashboards for tracking the efficiency of AML checks and monitoring the AML department’s workload.Stack: SQL (Greenplum/ClickHouse), Python, Tableau, Zeppelin, JIRA, Confluence.

> Managed fixed income portfolios with assets under management (AUM) exceeding USD 100 million.> Designed, updated, and refined credit risk models to evaluate the quality of banks, corporations, sub-federal entities, and both domestic and foreign sovereign borrowers.> Integrated essential asset management data from diverse sources into comprehensive dashboards, encompassing portfolio positions, market quotes, client profiles, and other features.Stack: Python, SQL, Power BI