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Gilead Sciences

Makes medicines for HIV, liver disease and cancer

Manager, Data Science & AI Delivery Lead - Clinical Development and Medical Affairs

Data ScienceConfirmed live in the last 24 hours
Full-timeRaleigh, NC, USA

About the Job

Requirements

  • A 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, natural language processing 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, scientific and technical audiences.

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.

Desired 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.

About the Company

Gilead Sciences

Makes medicines for HIV, liver disease and cancer

Gilead Sciences is a biopharmaceutical company that discovers, develops and sells medicines for HIV, viral hepatitis and other liver diseases, cancer and inflammatory conditions. Its HIV business covers both treatment, led by the once-daily pill Biktarvy, and prevention, including Descovy and Yeztugo, a lenacapavir injection given twice a year. In cancer, its Kite unit makes CAR T-cell therapies from patients' own immune cells, and Trodelvy is an antibody-drug conjugate for breast cancer. Gilead earns revenue by selling its drugs to wholesalers, specialty pharmacies, hospitals and governments worldwide after regulatory approval. The company was founded in 1987 and is headquartered in Foster City, California.

Company size
10,001+
Company stage
IPO
Headquarters
Foster City, CA
Founded
1987

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