PData Scientist – RecSysb Remote, Portugal | Product Department /b /ppbr/ppAbout the role /ppOur client - they're looking for a Data Scientist specialising in bRecommendation Systems /b to join their global Data Science team — building large-scale, production-grade RecSys that impact millions of players worldwide, working alongside Data Scientists, Engineers and Data Engineers.
/ppbr/ppKey Responsibilities /pulliDesign, implement and optimise end-to-end recommendation pipelines (data ingestion to model inference) /liliBuild and maintain scalable ETL pipelines /liliDevelop, evaluate and continuously improve ML models for RecSys /liliResearch and prototype SOTA approaches to improve recommendation quality /liliIntegrate multi-modal data (behavioural, transactional, contextual) into models /liliDesign and analyse A/B tests; build dashboards to track model metrics and business KPIs /liliCollaborate with Data Engineers, Software Engineers and stakeholders /li /ulpbr/ppRequired Skills /pulliStrong bPython /b (production), including Pandas, Polars, NumPy, scikit-learn, PyTorch, TensorFlow, JAX, Hugging Face /liliEnd-to-end ML deployment on cloud platforms (bAzure, GCP or AWS /b) — ETL to monitoring /liliDeep learning–based recommender systems (next-item prediction, sequential models) /lilibSQL and NoSQL /b databases (PostgreSQL, Redshift, Snowflake, BigQuery, MongoDB, Cassandra) /liliUnit/integration testing (Pytest), CI/CD, Docker /li /ulpbr/ppBonus Points For /pulliLarge-scale RecSys (candidate generation, ranking, retrieval, personalisation) /liliPublications in deep learning at relevant conferences /liliTransformer-based models / LLMs applied to RecSys /liliDistributed training and big data tech (Spark, Kafka, Databricks) /liliMulti-modal models (text, images, audio) /li /ulpbr/ppWhat They Offer /pulliCompetitive comp based on experience /liliRemote-friendly, flexible hours /liliWork on state-of-the-art ML infrastructure at scale /liliOpen-source contribution opportunities /li /ul