About Me
Experienced Data Scientist with a strong background in machine learning, data analysis and statistical modeling. Proficient in Python and Pyspark programming languages for big data manipulation, visualization, and predic…
Experienced Data Scientist with a strong background in machine learning, data analysis and statistical modeling. Proficient in Python and Pyspark programming languages for big data manipulation, visualization, and predictive modeling. Proven track record of delivering data-driven solutions to drive business growth and improve decision-making processes. Strong knowledge of various machine learning algorithms, statistical techniques, and data visualization tools.
Experience
Data Scientist
Customer churn - led and implemented a project aimed at identifying potential churn clients, resulting in an 8% conversion of non-active clients;
Demand Forecast - implemented a product targeted at creating sales demand forecasts for over 15,000 SKUs using functional programming. Achieved a forecast accuracy rate of over 70;
Uplift modelling - developed an uplift model, leading to a 3% increase in conversion rate;
TelegramBot - automated routine reporting for functional directors by creating a Telegram bot based on SQL queries.
Data Scientist
Customer churn - led and implemented a project aimed at identifying potential churn clients, resulting in an 8% conversion of non-active clients.
Demand Forecast - implemented a product targeted at creating sales demand forecasts for over 15,000 SKUs using functional programming.
Achieved a forecast accuracy rate of over 70.
Uplift modelling - developed an uplift model, leading to a 3% increase in conversion rate.
TelegramBot - automated routine reporting for functional directors by creating a Telegram bot based on SQL queries.
Data Scientist
Fraud - automated business process for fraudulent actions identification by creating a Telegram bot based on streaming data with Kafka Broker.
B2B boost matrix - built a prediction matrix for increasing products sales to B2B clients based on internal and external data.
Used parsing of open sources (taxes, national statistics data) for accuracy.
Data Scientist
Geo Analytics - identified new potential clients and revenue streams using parsing of >20K legal entities geocoordinates from open sources.
Visualized it in HTML maps.