Lead Data Science Manager – Life Sciences AI

Elsevier

Amsterdam

Presencial

EUR 79.000 - 132.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

Elsevier in Amsterdam and London is seeking a Manager Data Science to lead a team delivering production-ready data science solutions for Life Sciences products across pharma, biology, and clinical domains.

You will set direction, coach analysts, collaborate with product and engineering, and apply modern AI methods including NLP, knowledge graphs, embeddings, and GenAI to create measurable business impact.

Formación

  • Master’s or PhD in Computer Science, Data Science, or a related field.
  • 5+ years in data science, ML, NLP, or applied AI.
  • Experience leading technical teams.
  • Strong knowledge of Python and ML/NLP frameworks.
  • Experience with large structured and unstructured datasets.
  • Ability to manage multiple projects and stakeholders.
  • Excellent communication and leadership skills.
  • Experience with LLMs, GenAI, or RAG workflows.
  • Familiarity with Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, MLflow.

Responsabilidades

  • Lead and develop a team of data scientists.
  • Set strategy, priorities, and operating rhythm for the team.
  • Oversee data science delivery across ML, NLP, search, and knowledge graphs.
  • Collaborate with product, engineering, and domain experts to deliver production-ready solutions.

Conocimientos

Data science leadership
Python
NLP
GenAI
LLMs
Knowledge graphs
Team management
Experimentation
Communication

Educación

Master’s or PhD in Computer Science / Data Science

Herramientas

Databricks
PyTorch
Hugging Face
LangChain
LangGraph
Haystack
MLflow

Descripción del empleo

Elsevier in Amsterdam and London is seeking a Manager Data Science to lead a team delivering production-ready data science solutions for Life Sciences products across pharma, biology, and clinical domains.

You will set direction, coach analysts, collaborate with product and engineering, and apply modern AI methods including NLP, knowledge graphs, embeddings, and GenAI to create measurable business impact.

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