Data Scientist – RecSys

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Design, implement, and enhance comprehensive recommendation pipelines, covering everything from data ingestion to model inference.

• Construct and sustain scalable ETL pipelines to ensure dependable and efficient data flows.

• Develop, assess, and continually refine machine learning models tailored for recommendation systems.

• Investigate, prototype, and apply cutting-edge techniques to enhance recommendation quality and business metrics.

• Scale and improve data and model pipelines to handle large data volumes and facilitate real-time or batch processing.

• Integrate behavioral, transactional, and contextual signals from diverse systems into recommendation models.

• Conduct unit and integration testing across data, modeling, and deployment workflows.

• Oversee and preserve data pipelines, model quality, overall system performance, and downstream effects.

• Design and analyze A/B tests to assess model performance and inform data-driven product decisions.

• Create dashboards and observability tools to monitor model metrics, system health, and business KPIs.

• Collaborate with Data Engineers, Software Engineers, and stakeholders to produce scalable, production-ready solutions.

⛳️ Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.

• Proficient in Python with recent production experience.

• Practical experience with data science and machine learning libraries and frameworks, such as Pandas, Polars, NumPy, scikit-learn, PyTorch, TensorFlow, JAX, and Hugging Face.

• Familiarity with constructing and deploying end-to-end machine learning systems on cloud AI platforms like Azure, GCP, or AWS.

• Experience with ETL pipelines, deployment and monitoring, model versioning, and experiment tracking.

• Background in supporting batch or real-time workflows.

• Strong grasp of deep learning-based recommender systems for next-item prediction.

• Understanding of similar NLP architectures that model sequential patterns and context.

• Experience in developing efficient data transformation pipelines for OLTP and OLAP workloads.

• Solid knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, Redshift, Snowflake, BigQuery, MongoDB, and Cassandra.

• Experience with unit and integration testing frameworks, such as Pytest.

• Familiarity with CI/CD pipelines.

• Experience with Docker-based containerization.

🏝️ Benefits

• Opportunities for growth at all levels.

• Continuous investment in employee development.

• Strategic partnerships that create new avenues for success.