AI Manager

Hybrid opportunity with office all across the East Coast

We’re looking for an experienced R&D AI Manager to help pharmaceutical and biotechnology organisations translate advances in artificial intelligence, machine learning and data science into meaningful business and scientific outcomes.

This is an exciting opportunity for someone who combines strong hands-on technical expertise with life sciences domain knowledge, client leadership and a passion for innovation. You’ll work at the intersection of AI, Clinical Development and Medical Affairs, helping clients identify high-value opportunities, design fit-for-purpose solutions and scale AI from proof of concept to real-world impact.

You’ll also play a key role in shaping AI strategy, developing new offerings, mentoring talented teams and contributing to the continued growth of a specialist life sciences consulting practice.

What you’ll do

AI strategy and solution design

Design, develop and deploy AI/ML solutions across the R&D value chain, particularly within Clinical Development and Medical Affairs.
Translate complex scientific and business challenges into scalable, decision-focused AI solutions, working with clinical, operational, real-world, literature and medical content data.
Embed appropriate governance, validation, explainability and regulatory considerations into solution design and delivery.

Data science and AI leadership

Define and execute data science strategies aligned with client R&D and Medical priorities, balancing scientific rigour, business value and practical feasibility.
Lead the development of diagnostic, predictive, prescriptive and generative AI solutions, selecting appropriate methods based on the problem and available data.
Ensure analytical models are robust, explainable, validated and suitable for deployment in regulated life sciences environments.

Client engagement and commercial growth

Build trusted relationships with senior stakeholders across R&D, Medical Affairs, Digital and Data Science.
Lead or contribute to proposals, RFPs, proofs of value and pilots, articulating compelling business cases and demonstrating the practical value of AI.
Advise clients on AI opportunity assessment, use-case prioritisation, strategic roadmaps and the transition from experimentation to scaled adoption.
Partner with consulting, technology and product teams to develop integrated solutions and identify opportunities for continued client engagement.

Programme delivery and team leadership

Own end-to-end project delivery, including scoping, planning, prioritisation, risk management and quality assurance.
Lead, mentor and develop junior data scientists and analysts, promoting high standards of analytical excellence, storytelling and client service.
Coordinate cross-functional teams to deliver high-quality outcomes in complex, multi-stakeholder environments.

Innovation and capability building

Develop reusable data science assets, accelerators and frameworks that improve the scalability and consistency of AI delivery.
Monitor developments in AI/ML, life sciences R&D and relevant regulatory expectations, translating emerging opportunities into practical client solutions.
Contribute to thought leadership through publications, white papers, conference presentations and perspectives on Clinical AI, Medical AI and evidence generation.

Communication and influence

Translate complex analytical findings into clear, compelling recommendations for both technical and non-technical audiences.
Develop executive-ready presentations, visualisations and narratives that connect AI outputs to measurable scientific, operational and commercial outcomes.
Influence senior stakeholders and help organisations make confident, evidence-based decisions about AI investment and implementation.

What you’ll bring

Experience and domain expertise

Approximately 6–10 years of experience in data science, advanced analytics or applied AI, including at least two years leading people, projects or workstreams.
Experience applying analytics and AI within pharmaceutical or biotechnology organisations, ideally across Clinical Development and/or Medical Affairs.
Understanding of regulated life sciences environments, including data quality, validation, traceability and compliance considerations.
The ability to connect technical innovation with scientific needs, operational realities and measurable business outcomes.

Technical and analytical expertise

Strong hands-on experience with statistical and machine learning methods, including regression, classification, clustering and predictive modelling.
Proficiency in Python and/or R, alongside strong working knowledge of SQL.
Familiarity with data science and machine learning frameworks such as scikit-learn, TensorFlow or PyTorch.
Experience with statistical programming environments such as Python, R, SAS, MATLAB or equivalent.
Ability to work with structured and unstructured datasets, including clinical, operational, real-world, textual and medical content data.
Sound judgement in selecting analytical techniques that are appropriate to the problem, data availability and intended use.

Client and commercial leadership

Experience contributing to or leading proposals, RFP responses, proofs of value and pilot programmes.
Confidence engaging directly with clients, shaping problem statements and communicating the value and feasibility of technical solutions.
Strong relationship-building skills and the ability to identify opportunities for further client impact and business growth.

Delivery and people leadership

Proven project management capabilities, including scope definition, prioritisation, risk management and quality assurance.
Experience mentoring or developing data science and analytics professionals.
Confidence working across multidisciplinary teams spanning consulting, technology, product and life sciences subject matter experts.

Personal attributes

Excellent written and verbal communication skills, including