Data Scientist - RecSys

What you will do 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. What you bring 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 libraries and framewor