Incentive Compensation Manager
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As Manager Data Science, you will lead a data science team within Elsevier's Corporate Markets Life Sciences portfolio, guiding strategy, delivery, and people development. You will drive production-ready AI solutions across ML, NLP, knowledge graphs, and GenAI in collaboration with product, engineering, and domain experts. Your work supports Life Sciences customers by delivering measurable impact and scalable data-enabled capabilities. You will foster rigorous, responsible AI practices and cross-functional collaboration to advance discovery and health outcomes.
Arbeidsvoorwaarden / Benefits- flexible working hours
- wellbeing initiatives
- shared parental leave
- study assistance
- sabbaticals
- location-specific benefits
- Lead and develop a team of data scientists, shaping strategy, priorities, and delivery across multiple projects
- Establish strong data science practices for experimentation, evaluation, data quality, and production collaboration
- Oversee diverse data science work including ML, NLP, NLP pipelines, knowledge graphs, search, ranking, and GenAI solutions
- Ensure robust, scalable, production-ready solutions and close collaboration with engineering and domain experts
- Define evaluation methods and metrics for model quality, retrieval and business impact; guide offline and online experimentation
- Promote responsible AI (transparency, fairness, privacy, risk management) and evidence-based stakeholder communication
- Collaborate with product managers, engineers, content experts, ontology specialists, and business stakeholders to translate needs into data science plans
- Represent the team in cross-functional planning and contribute to Life Sciences AI strategy
- Master's or PhD (or equivalent experience) in a relevant field; 5+ years in data science, ML, NLP, or AI
- Experience leading technical teams and delivering cross-functional projects
- Strong knowledge of supervised/unsupervised learning, GenAI, model evaluation, experimentation
- Proficiency in Python and common data science/NLP frameworks
- Experience with large structured/unstructured datasets and multi-project delivery
- Excellent communication and stakeholder management skills; ability to coach and improve team practices
- Experience with LLMs, RAG pipelines, embeddings, GenAI evaluation, or human-in-the-loop workflows
- Experience with tools/platforms such as Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, MLflow or similar
- leadership
- stakeholder management
- communication
- machine learning
- NLP
- statistical modelling
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