Aleksandr Smetanin

• Developed a model of product demand elastisity based on price and market indicators • Designed a model for loan margin recommendation based on industry and segment as a baseline for managers • Performed customer segmentation and clustering • Provided data-driven insights on business growth and opportunities • Collected data from multiple sources, performed cleaning and exploration, created reports

• Implemented, deployed and maintained models for retail recommendations • Developed data processing pipelines with pyspark, azure and pandas • Developed a GraphQL backend using Aiohttp, Tartiflette, PostgreSQL and Docker • Developed a REST API using FastAPI and Gino/SQLalchemy for PostgreSQL to store data for AWS pipeline orchestration systems • Developed, automated and maintained unit and integration tests with pytest • Participated in mentoring and giving lectures to Python internship groups