About this role
Manager, Data Science & AI Delivery Lead – Clinical Development and Medical Affairs
As part of our enterprise AI strategy to speed life-changing therapies to patients, we are seeking a Manager, Data Science & AI Delivery Lead to design, develop and deliver advanced analytics, machine learning and generative AI solutions across Clinical Development and Medical Affairs. This role combines hands-on data science leadership with end-to-end delivery accountability, translating high-value business and scientific problems into validated, scalable and adopted data products.
The successful candidate will lead data exploration, feature engineering, model development, experimentation and evaluation while coordinating multidisciplinary teams from discovery through production. The role will partner with clinical, medical and technology stakeholders to ensure solutions are scientifically credible, technically robust, compliant, measurable and integrated into business workflows.
This position is based in Raleigh, North Carolina (hybrid-eligible).
Key Responsibilities
- Lead discovery with Clinical Development and Medical Affairs stakeholders to define analytical questions, hypotheses, target outcomes, success measures and product requirements.
- Perform hands-on data exploration, data preparation, feature engineering, statistical analysis and model prototyping using clinical, operational, medical and scientific datasets.
- Design, develop and evaluate machine learning, natural language processing and generative AI solutions appropriate to the business problem, data quality and regulated context.
- Establish rigorous experimentation and evaluation approaches, including baseline comparisons, error analysis, robustness testing, explainability, bias assessment and human-in-the-loop review.
- Translate prototypes into production-ready solutions by partnering with data engineering, MLOps, architecture, platform, security, privacy and quality teams.
- Own end-to-end delivery for assigned data science and AI products, including scope, roadmap, backlog, sprint execution, dependencies, release readiness, adoption and continuous improvement.
- Develop epics, user stories, acceptance criteria and validation evidence that connect model performance to user needs and measurable business or scientific outcomes.
- Guide data scientists and delivery partners on analytical methods, coding quality, reproducibility, documentation, model evaluation and responsible AI practices.
- Support development and monitoring of data pipelines, feature stores, model services, APIs and analytical applications using approved enterprise platforms.
- Define and track data quality, model performance, drift, reliability, user adoption, cycle-time improvement and value-realization metrics.
- Ensure solutions comply with applicable data governance, privacy, security, validation and GxP requirements.
- Maintain model documentation, experiment records, technical specifications, operating procedures and production-support runbooks.
- Manage vendors and co-sourced teams, remove delivery blockers, escalate risks and communicate technical trade-offs and progress to stakeholders and leadership.
Skills and Experiences
- Bachelor’s degree in data science, statistics, computer science, engineering, applied mathematics, bioinformatics, life sciences or a related discipline and 6+ years of relevant experience; or a master’s degree and 4+ years of relevant experience.
- Hands-on experience developing statistical, machine learning, NLP or generative AI solutions using Python, SQL and commonly used data science libraries.
- Experience with supervised and unsupervised learning, experimental design, feature engineering, model evaluation, error analysis and interpretation of analytical results.
- Experience delivering data science products from problem definition and prototyping through production deployment, monitoring, adoption and enhancement.
- Working knowledge of data pipelines, cloud platforms, APIs, version control, automated testing, model lifecycle management and MLOps practices.
- Experience leading Agile delivery, including roadmap development, backlog prioritization, sprint planning, release coordination, dependency management and risk escalation.
- Ability to assess data fitness and communicate uncertainty, model limitations, technical trade-offs and recommendations clearly.
- Strong stakeholder management and communication skills across clinical, medical and technical audiences.
Preferred Qualifications
- Experience applying data science or AI in Clinical Development, clinical operations, clinical data management, biostatistics, safety, regulatory, quality or Medical Affairs.
- Experience with clinical trial, real-world, medical insights, publications, scientific literature or other life sciences datasets.
- Experience in a GxP-regulated environment and familiarity with model documentation, privacy, validation and responsible AI controls.
- Experience with Databricks, AWS, MLflow, vector search, retrieval-augmented generation or large language model evaluation.
- Familiarity with Veeva, clinical trial management systems, electronic data capture platforms, safety systems or CRM platforms.
- Experience leading vendors or co-sourced technical teams and establishing measurable adoption and business-value outcomes.
The salary range for this position is: $126,565.00 - $163,790.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*.
For additional benefits information, visit:
https://www.gilead.com/careers/compensation-benefits-and-wellbeing
- Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
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Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, s