Senior AI Scientist - Biomedical Causal Reasoning

Boehringer Ingelheim Pharmaceuticals, Inc.; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work arrangement

Job summary

Boehringer Ingelheim is seeking a Senior Staff AI Scientist in London within the AI Reasoning team. You will apply state-of-the-art large language models, AI assistants and evidence-retrieval to explain and rationalise model outputs, turning them into trusted scientific hypotheses.

You will lead multidisciplinary squads, set scientific standards, mentor researchers, and ensure biology-driven decisions align with portfolio needs.

Qualifications

• PhD in Computational Biology, Bioinformatics, ML or related field.
• Industry pharma/biotech experience with target identification & biomarker discovery.
• Experience using modern AI tools for scientific work (LLMs, AI assistants, retrieval-augmented reasoning).
• Proven ability to lead without formal authority and mentor senior AI scientists.
• Excellent communication bridging AI and biology audiences.

Responsibilities

• Translate strategy into a scientific roadmap and drive delivery.
• Strengthen AI-generated hypotheses with evidence, provenance and biological context.
• Lead the development of evaluation and benchmarking approaches for evidence credibility.
• Partner with computational biology and human genetics to meet real disease-biology needs.
• Provide senior leadership and mentoring; build external credibility in AI-assisted reasoning.

Skills

Scientific leadership

Mentoring senior AI scientists

Communication

Translational biology

Regulatory understanding AI in life-sc

Education

PhD in Computational Biology, Bioinformatics, Machine Learning or related field

Tools

Retrieval-augmented reasoning

Biomedical knowledge graphs

Ontologies / pathway resources

Job description

Boehringer Ingelheim is seeking a Senior Staff AI Scientist in London within the AI Reasoning team. You will apply state-of-the-art large language models, AI assistants and evidence-retrieval to explain and rationalise model outputs, turning them into trusted scientific hypotheses.

You will lead multidisciplinary squads, set scientific standards, mentor researchers, and ensure biology-driven decisions align with portfolio needs.