Mid-Senior Data Scientist (Life Sciences)

Your role

Capgemini Engineering is looking for a Mid-Senior Data Scientist with a strong background in biomedical sciences and data engineering to join its growing team in Portugal. The role focuses on designing, building, and governing data foundations for life sciences projects, connecting scientific, engineering, and product stakeholders through robust, scalable, and FAIR data solutions.

• Design and govern biomedical data models, including source-to-canonical mapping, ontology alignment, schema versioning, changelogs, and downstream impact assessments.
• Build and maintain schema-driven data pipelines in Python and SQL, conduct exploratory data analysis, and implement validation frameworks.
• Develop knowledge graphs using RDF, OWL, SPARQL, Neo4j, and GraphDB.
• Apply machine learning and Gen AI tools, including text generation APIs, chatbots, and enterprise search solutions.
• Design FAIR data products with persistent identifiers and provenance.
• Align scientific, engineering, and product stakeholders through clear communication and structured documentation.
• Work with biomedical ontologies and controlled vocabularies such as Ensembl, UniProt, and Gene Ontology.

Your profile

• MSc or PhD in Bioinformatics, Biomedical Engineering, Molecular or Cell Biology, Neuroscience, Genetics, or a related field.
• Experience with biomedical data modelling, harmonisation, ontology alignment, persistent identifiers, and provenance.
• Strong Python and SQL skills, with experience building data pipelines and performing exploratory data analysis.
• Applied data science or machine learning experience relevant to knowledge graph or scientific data work.
• Strong stakeholder management and communication skills.
• Fluent in Portuguese and English.
• Experience in pharmaceutical or biotech organisations, FAIR data products, knowledge graphs, schema governance, LinkML, ML frameworks, or Gen AI tools is desirable.

What you'll love about working here

• Multicultural and inclusive team environment.
• Supportive atmosphere promoting work-life balance.
• National and international projects.
• Hybrid work.
• Career growth, training, and certification programmes.
• Health and life insurance.
• Referral programme with bonuses.