Data Scientist - RecSys

Arrise
Portugal
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Collaboration"]

Design and optimize end-to-end recommendation pipelines for next-item prediction, from data ingestion and scalable ETL through model inference and monitoring. Build and improve ML models for recommender systems using deep learning and NLP-like sequential architectures, integrate multi-modal behavioral/transactional/context signals, and evaluate impact with A/B tests. Collaborate with data and software engineering to deliver production-ready, reliable systems with dashboards and observability.

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FursaFursa
Arrise
Arrise
1 month ago

Data Scientist - RecSys

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Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live
Reposted: similar role first listed 4 months ago

Job Summary

Design and optimize end-to-end recommendation pipelines for next-item prediction, from data ingestion and scalable ETL through model inference and monitoring. Build and improve ML models for recommender systems using deep learning and NLP-like sequential architectures, integrate multi-modal behavioral/transactional/context signals, and evaluate impact with A/B tests. Collaborate with data and software engineering to deliver production-ready, reliable systems with dashboards and observability.
Location: Portugal
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design, implement, and optimize end-to-end recommendation pipelines from data ingestion to model inference.
  • •Build and maintain scalable ETL pipelines to support reliable data flows for real-time and batch processing.
  • •Develop, evaluate, and continuously improve ML models for recommendation systems, including multi-modal data integration.
  • •Design and analyze A/B tests to evaluate model performance and enable data-driven product decisions.
  • •Monitor and maintain end-to-end system performance (data pipelines, model quality, and downstream impact) and build dashboards/observability tools.

Key Requirements

  • •Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • •Strong Python experience with production use and hands-on work with data science/ML libraries and frameworks (e.g., Pandas, Polars, NumPy, scikit-learn, PyTorch, TensorFlow, JAX, Hugging Face).
  • •Experience building and deploying end-to-end ML systems on cloud AI platforms (Azure, GCP, or AWS), including ETL to deployment, monitoring, model versioning, and experiment tracking.
  • •Strong understanding of deep learning recommender systems for next-item prediction and sequential/context modeling architectures.
  • •Experience with unit/integration testing (e.g., Pytest), CI/CD pipelines, and Docker-based containerization.
Experience:IGamingRecommendation systemsMachine learningDeep learning
Education:
Skills:Collaboration
Tech Stack:PythonPandasPolarsNumPyScikit-learnPyTorchTensorFlowJAXHugging FaceAzureGCPAWSSQLPostgreSQLMySQLRedshiftSnowflakeBigQueryMongoDBCassandra

Company Brief

Arrise
Arrise provides a cloud platform that helps property owners, facilities teams and compliance managers centralize building safety, maintenance and regulatory documentation, automate inspections and workflows, and streamline reporting to reduce risk and ensure operational compliance.
Industry: Facility Management
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