Data Scientist - RecSys

• Design, implement, and optimize end-to-end recommendation pipelines, from data ingestion to model inference.
• Build and maintain scalable ETL pipelines to support reliable and efficient data flows.
• Develop, evaluate, and continuously improve ML models for recommendation systems.
• Research, prototype, and implement state-of-the-art (SOTA) approaches to improve recommendation quality and drive key business metrics.
• Scale and optimize data and model pipelines to handle large volumes of data and real-time or batch processing needs.
• Integrate multi-modal data (e.g., behavioral, transactional, and contextual signals) from various systems into recommendation models.
• Ensure robustness and stability of pipelines by implementing unit and integration tests across data, modeling, and deployment workflows.
• Monitor and maintain end-to-end system performance, including data pipelines, model quality, and downstream impact.
• Design and analyze A/B tests to evaluate model performance and support data-driven product decisions.
• Build dashboards and observability tools to track model metrics, system health, and business KPIs.
• Collaborate closely with Data Engineers, Software Engineers, and stakeholders to deliver scalable, production-ready solutions.

Bachelor's or Master's degree in Computer Science, Engineering, or a related field Strong Python experience with recent production use, including hands-on work with data science and machine learning librarie