Data Scientist – RecSys

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

📋 Description

• Design, implement, and enhance comprehensive recommendation pipelines that cover data ingestion to model inference.

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

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

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

• Scale and optimize data and model pipelines to handle large data sets and support real-time or batch processing.

• Incorporate behavioral, transactional, contextual, and other multi-modal data into recommendation algorithms.

• Execute unit and integration tests throughout data, modeling, and deployment processes.

• Oversee and maintain data pipelines, ensuring model quality, system performance, and assessing downstream impacts.

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

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

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

⛳️ Requirements

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

• Proficient in Python with recent hands-on experience in production environments.

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

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

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

• Experience in supporting batch or real-time machine learning workflows.

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

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

• Proven experience in building efficient data transformation pipelines for both transactional (OLTP) and analytical (OLAP) workloads.

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

• Experience with unit and integration testing, particularly with Pytest.

• Familiarity with CI/CD pipelines and Docker-based containerization.

• Experience in developing large-scale recommender systems is a plus.

• Publications in deep learning at relevant conferences or journals are advantageous.

• Familiarity with Azure Data Factory, AWS Glue, or Google Cloud Dataflow is a plus.

• Experience in designing and analyzing A/B tests and understanding relevant evaluation metrics is beneficial.

• Experience in designing and implementing metadata-driven pipelines to scale automated A/B testing systems is advantageous.

• Experience in developing multi-modal models that integrate text, images, audio, or other data types is beneficial.

• Experience applying transformer-based models or LLMs to recommendation or personalization tasks is an advantage.

• Familiarity with distributed training, including data parallelism and model parallelism, is a plus.

• Experience with distributed data processing and big data technologies such as Spark, Hadoop, Flink, Kafka, Hive, Presto, or Databricks is an advantage.

🏝️ Benefits

• Opportunity to work with cutting-edge technologies in the field of machine learning and data science.

• Collaborative and innovative work environment.

• Professional development and growth opportunities.

• Competitive salary and comprehensive benefits package.