> Markdown version of [/jobs/ext/2120352-director-biopharma-data-science](https://www.wearedevelopers.com/jobs/ext/2120352-director-biopharma-data-science). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, Biopharma Data Science - **Company:** Owkin, Inc. - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, Bioinformatics, Clinical Data Repository, Computational Biology, Databases, Python (Programming Language), Machine Learning, ReactJS, Large Language Models, Multi-Agent Systems, Deep Learning, Information Technology, Virtual Agents - **Published:** August 19, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pda07ngf35 ## About the Role 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., * 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. ## Description 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. ## Related Videos - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Building Agentic Applications: A Deep Dive into Zooka, an AI Cardiologist Assistant](https://www.wearedevelopers.com/videos/2030-building-agentic-applications-a-deep-dive-into-zooka-an-ai-cardiologist-assistant) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)