Senior Data Scientist (Pricing)

• Manage end-to-end ML projects: problem definition → solution → testing → deployment → support. • Work with data engineers to build datasets and define data requirements, and assess. feasibility, risks, and constraints • Work with data analysts to design and analyze A/B tests: metrics, splits, interpretation of results, and recommendations for deploying solutions. • Develop and train models (classic ML + DL), including solutions for text and image embeddings; conduct offline evaluation and error analysis. • Deploy the model and code to production (Python service), support releases and integrations. • Be responsible for model quality post-launch: metrics, monitoring, drift/degradation, improvement plans, and support procedures.