Director, Biopharma Data Science

ABOUT US Owkin is an agentic AI company pioneering Biological Artificial Superintelligence to solve problems in biology where human researchers alone have failed. Owkin builds K Pro - an AI scientist for pharmaceutical research and strategic decision-making. K Pro orchestrates a suite of AI skills and tools to decode complex biology, accelerate research, and dramatically increase productivity. K Pro is built on Owkin’s unrivalled multimodal patient data network, state-of-the-art AI for biology and a decade of experience working with pharmaceutical partners. Please submit your CV in English ABOUT THE ROLE: We are looking for a visionary Director, Biopharma Data Science to champion the development of our AI Scientist, an agentic system designed to navigate the complexities of target and drug discovery. You will lead a squad of data/research/AI scientists at the interface of machine learning and computational biology, working as both builders of and expert internal users of Owkin's K Pro platform on real scientific use cases. You’ll be at the heart of Owkin’s mission, collaborating with Owkin’s scientists and/or external collaborators (academic researchers/ pharmaceutical companies) to deliver our strategic projects, and creating the engine that will discover the next generation of life-saving therapeutics. This role is about building a "scientist in a box" that can reason over biological data, design experiments, and autonomously drive therapeutic breakthroughs.   IN PARTICULAR, YOU WILL: - Co-build the development of Owkin's AI Scientist, across two complementary discovery paradigms: - data-first discovery (deriving targets and pharmaceutical insights from multimodal patient data, across modalities and stages of clinical development) and - knowledge-first discovery (generating and testing novel scientific hypotheses grounded in the scientific literature, then validating them on data). - Lead and/or contribute to projects aiming to discover novel drug targets, biomarkers and disease subtypes through reverse translation based on patients’ multi-omics and pre-clinical data (genomics, transcriptomics -spatial, single-cell, bulk-, proteomics, and others) via multimodal analyses and machine / deep learning algorithms. - Collaborate closely with your biomedical team colleagues (biologists, MDs, computational chemists) and with Owkin's broader Research & Technology team (agentic engineers, software engineers, ML engineers, and others). - Contribute scientific input to help anticipate and shape the tools and capabilities our pharmaceutical partners will need, in coordination with Owkin's client-facing teams. - Communicate your scientific results internally and externally. - Participate in extending Owkin's methodology, including but not limited to regular literature review. - Develop and retain a high performing and engaged scientists team.    ABOUT YOU: The successful candidate is independent, deeply curious, and obsessed with the idea of automating the scientific method. You don’t just wait for the perfect dataset, you build the tools to have it. CORE REQUIREMENTS: - Technical Foundation: PhD in Bioinformatics, Computational Biology, or Data Science, Computer Science, Machine Learning but with strong knowledge of Computational Biology (or equivalent high-level industry experience). - Deep expertise on multimodal datasets, especially on different omics modalities (bulkRNA seq, single cell, spatial transcriptomic, WGS, WES, GWAS, proteomics, …). - The Toolkit: - Expert-level Python skills with a focus on "building". - Comfortable writing clean, modular code that interfaces with complex APIs and databases. - Publication Record: History of contributions to top-tier journals and conferences. - Communication: - Ability to explain complex agent behaviors to both AI and biological experts. - Excellent written and oral communication skills. - Fluent in English (French is a plus). - Stakeholder Management: Able to manage expectations from stakeholders at all levels, including cross-functional teams within Owkin. - Team first, highly collaborative mindset. PREFERRED QUALIFICATIONS (THE "BIG PLUS") - Expertise in Agentic AI: Deep understanding of LLM reasoning (Chain-of-Thought, ReAct), long-context management, and tool-augmented generation. - Transverse knowledge: Good understanding or previous experience on other data modalities relevant for medical purposes and drug discovery (H&E, EHR, …) - Systems Engineering: Experience training and deploying large-scale models and managing complex multi-agent orchestrations. - Causal Inference: Experience in understanding "response to treatment" and causal discovery in biological systems. - Industry Impact: Proven track record of taking a research concept and turning it into a functional tool used by other scientists.    Ref: #LI-HB1 WHAT WE OFFER