R&D AI Manager

What you'll doAI Strategy & Solution Design

• Design, build, and deploy AI/ML solutions across the R&D value chain, with a focus on Clinical Development and/or Medical Affairs (e.g., trial design, clinical operations, evidence generation, medical content, scientific engagement), ensuring regulatory- and compliance-by-design delivery.
• Translate complex R&D and Medical problems into scalable, decision‑centric AI solutions, integrating structured and unstructured data (clinical, operational, real‑world, literature, and medical content).

• Define and execute data science strategies aligned to R&D and Medical priorities, balancing scientific rigor, business impact, and operational feasibility.
• Lead the development of diagnostic predictive, prescriptive, and generative models, applying appropriate techniques based on the problem definition and available data.
• Ensure models are explainable, validated, and production‑ready within regulated life sciences environments.

• Lead and contribute to RFPs, proposals, POVs, and pilots, shaping compelling AI narratives grounded in client value and real‑world feasibility.
• Serve as a trusted advisor to client stakeholders in R&D, Medical, and Digital, helping them prioritise AI use cases, design road‑maps, and move from pilots to scaled impact.
• Partner closely with consulting, technology, and product teams to drive integrated, cross‑functional delivery.

• Own end‑to‑end project execution, including scoping, delivery planning, risk management, and quality assurance, ensuring on‑time, high‑impact outcomes.
• Mentor and guide junior data scientists and analysts, setting high standards for analytical quality, storytelling, and client engagement.

• Play a key role in building repeatable data science assets, accelerators, and platforms that scale AI delivery across Clinical Development and Medical Affairs.
• Stay current on advances in AI/ML, life sciences R&D, and evolving regulatory expectations, proactively translating these into new offerings and differentiated client value.
• Contribute to internal and external thought leadership, including whitepapers, conference presentations, and publications in areas such as Clinical AI, Medical AI, and evidence generation.

• Communicate complex analytical findings clearly to technical and non-technical audiences through executive‑ready narratives, visualisations, and recommendations.
• Influence senior stakeholders by connecting AI outputs to decisions, actions, and measurable R&D or Medical outcomes.

• 6-10 years of experience in data science, advanced analytics, or applied AI, with at least 2 years in a people‑ or work‑stream‐leadership role within the life sciences industry.
• Demonstrated experience applying analytics and AI in pharmaceutical or biotech R&D, with exposure to Clinical Development and/or Medical Affairs strongly preferred.
• Strong understanding of regulated R&D environments, including data quality, validation, traceability, and compliance considerations.

• Deep hands‑on experience with statistical and machine learning methods, including regression, classification, clustering, and predictive modelling.
• Proficiency in Python and/or R, with strong working knowledge of SQL; experience with common ML and data science frameworks (e.g., Tensor Flow, PyTorch, scikit‑learn) preferred.
• Prior experience with statistical programming tools such as R, SAS, Python, MATLAB, or equivalent, and the ability to select appropriate techniques for the problem at hand.
• Ability to work across structured and unstructured data, including clinical, operational, real‑world, text, and medical content data.

• Proven track record of contributing to or leading RFP responses, proposals, POVs, and pilots, translating technical capabilities into compelling client value narratives.
• Experience engaging directly with client stakeholders, with the ability to shape problem statements, influence decisions, and build long‑term trusted relationships.