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Data Scientist – Machine Learning & Personalization

Jobgether

Remote
Remote 🇬🇧 English
Python pandas NumPy scikit-learn SQL AWS Microsoft Azure

Descripcion del puesto

About the role

We are seeking a Data Scientist to join a fast‑paced, product‑driven team in Spain. In this remote‑first position you will design, develop and productionize machine‑learning systems that power personalization, search and recommendation features for a global user base.

Key responsibilities

  • Develop, implement and productionize ML models that improve personalization, search ranking and recommendation systems.
  • Design data‑driven algorithms to enhance user experience and drive measurable engagement and conversion improvements.
  • Apply advanced statistical and data‑mining techniques to extract insights from large‑scale datasets.
  • Collaborate with engineering and product teams to integrate models into production, ensuring scalability and reliability.
  • Monitor model performance, iterate based on real‑world data and business feedback.
  • Support cloud infrastructure and data pipelines for scalable ML workflows.
  • Contribute to A/B testing frameworks to validate model effectiveness.

Required profile

  • Minimum 2 years of experience as a Data Scientist, Quantitative Analyst or similar role.
  • Strong proficiency in Python and its data‑science ecosystem (pandas, NumPy, scikit‑learn or equivalents).
  • Solid foundation in probability, statistics, machine learning and linear algebra.
  • Proven track record of applying ML models to real‑world business problems with measurable impact.
  • Good knowledge of SQL and experience with relational databases.
  • Experience with cloud platforms such as AWS, GCP or Microsoft Azure is highly desirable.
  • Ability to work in a fast‑paced, product‑oriented environment and communicate technical concepts to non‑technical stakeholders.
  • Bachelor’s or Master’s degree in a quantitative field (e.g., Applied Mathematics, Computer Science, Engineering).

Required skills

  • Python
  • pandas
  • NumPy
  • scikit‑learn
  • SQL
  • AWS
  • Google Cloud Platform
  • Microsoft Azure

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