Manager Data Science

Location: London Wall, United Kingdom

Salary: €79,000–€131,500 annual base pay range if performed in Amsterdam, Netherlands.

Company

hirify.global provides trusted content, data, analytics, and technology for research, healthcare, and life sciences.

What you will do

• Lead, coach, and develop a team of data scientists across multiple projects and product areas.
• Set team strategy, priorities, delivery plans, and data science operating practices.
• Oversee machine learning, statistical modelling, NLP, search, recommendation, knowledge graph, and generative AI solutions.
• Guide models and pipelines for classification, entity extraction and linking, ranking, document understanding, enrichment, prediction, and decision support.
• Partner with product, engineering, content, ontology, biomedical, and commercial stakeholders to deliver production-ready solutions.
• Promote responsible AI, scientific rigor, clear communication, and continuous improvement.

Requirements

• Master’s degree, PhD, or equivalent practical experience in computer science, data science, machine learning, statistics, bioinformatics, cheminformatics, information retrieval, or a related field.
• Significant experience in data science, machine learning, NLP, statistical modelling, information retrieval, or applied AI.
• Experience directly managing or leading technical teams and coaching data scientists.
• Strong knowledge of model evaluation, experimentation, supervised and unsupervised learning, GenAI, and statistical analysis.
• Practical Python experience and familiarity with large structured and unstructured datasets.
• Experience with LLMs, RAG pipelines, embeddings, GenAI evaluation, human-in-the-loop workflows, or tools such as Databricks, PyTorch, Hugging Face, LangChain, LangGraph, Haystack, and MLflow.

Nice to have

• Experience in life sciences, pharmaceuticals, chemistry, biomedical research, or clinical data.
• Knowledge of ontologies, taxonomies, controlled vocabularies, metadata standards, semantic enrichment, search, ranking, recommendation, or knowledge graphs.
• Exposure to production ML systems, MLOps, data pipelines, and model monitoring.

Culture & Benefits

• Flexible working hours to support personal productivity and work-life balance.
• Wellbeing initiatives and shared parental leave.
• Study assistance and sabbaticals.
• Country-specific benefits and an accessible hiring process.