Manager Data Science (Life Sciences)

Location: Amsterdam or London

Salary: €79,000–€131,500 annual base pay for Amsterdam, covered by the Collective Labor Agreement Publishing Industry.

Company

hirify.global provides trusted scientific, clinical, and healthcare content, data, and analytics for researchers, clinicians, and life sciences professionals.

What you will do

• Lead, coach, and develop a team of data scientists while setting strategy, priorities, resources, and delivery practices.
• Guide machine learning, statistical modelling, NLP, neural network, search, recommendation, knowledge graph, and generative AI work across Life Sciences products.
• Oversee models and pipelines for classification, entity recognition and linking, document understanding, ranking, extraction, enrichment, prediction, and decision support.
• Direct evaluation, experimentation, error analysis, annotation, A/B testing, and human-in-the-loop workflows.
• Partner with product, engineering, content, ontology, biomedical, and commercial stakeholders to deliver scalable, maintainable, production-ready solutions.
• Communicate technical findings, trade-offs, risks, and recommendations while contributing to the broader Life Sciences data science and AI strategy.

Requirements

• Master’s, PhD, or equivalent practical experience in Computer Science, Data Science, Machine Learning, Statistics, Bioinformatics, Cheminformatics, Information Retrieval, or a related field.
• At least 5 years of experience in data science, machine learning, NLP, statistical modelling, information retrieval, or applied AI.
• Experience directly managing or leading technical teams, coaching data scientists, reviewing technical work, and improving team practices.
• Strong understanding of supervised and unsupervised learning, generative AI, statistical analysis, model evaluation, and experimentation.
• Practical Python experience with common data science, machine learning, or NLP frameworks.
• Experience working with large, complex, structured and unstructured datasets and managing multiple projects through others.
• Strong communication and stakeholder management skills.
• Experience with LLMs, RAG pipelines, embeddings, GenAI evaluation, or human-in-the-loop annotation workflows.
• Experience with modern AI tools and platforms such as Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, MLflow, or similar.

Nice to have

• Experience in life sciences, pharmaceuticals, chemistry, biomedical research, or clinical data.
• Familiarity with ontologies, taxonomies, controlled vocabularies, and metadata standards.
• Experience with NLP, entity extraction, entity linking, semantic enrichment, search, ranking, recommendation, or knowledge graph methods.
• Exposure to production ML systems, MLOps, data pipelines, and model monitoring.

Culture & Benefits

• Flexible working hours to support individual productivity and work-life balance.
• Wellbeing initiatives, shared parental leave, study assistance, and sabbaticals.
• Country-specific benefits and support for long-term career development.
• Culture focused on scientific rigor, collaboration, responsible AI, customer focus, and continuous improvement.