Gilead Sciences · 18 hours ago
Associate Director, Marketing Sciences
United States - New Jersey - Parsippany
Full-time
Hybrid
Lead/Staff, Director/Executive
$178K/yr - $253K/yr
8+ years expGilead Sciences is committed to creating a healthier world for all people, tackling major health challenges through innovative therapies. The Associate Director, Marketing Sciences will lead the design and development of machine learning capabilities to enhance data-informed commercial decision making, focusing on HCP engagement and sales dynamics.
BiopharmaBiotechnologyHealth CareManufacturingPharmaceutical
Responsibilities
Lead the design, development, and scaling of omnichannel machine‑learning capabilities—including sales, content and engagement machine learning models, content‑ranking systems, and engagement prediction frameworks—to support data‑informed commercial decision making
Establish sustainable, reproducible methodologies for building and deploying ML solutions, ensuring long‑term maintainability and alignment with enterprise architecture and commercial strategy
Partner with Marketing Science measurement teams to incorporate analytical feedback, performance insights, and validation results into model enhancements and roadmap evolution—without owning measurement design itself
Conduct technical feasibility assessments for omnichannel solution development and collaborate with IT and Commercial Operations on buy‑vs‑build decisions
Define platform and infrastructure needs in partnership with IT, ensuring efficient data pipelines, model execution environments, and integration into commercial systems (e.g., CRM, orchestration platforms)
Serve as a commercial point of contact for enterprise‑wide ML policies, model governance, and data science integration workstreams, ensuring that omnichannel ML use cases adhere to regulatory and compliance requirements
Collaborate with global (US and ex‑US) affiliates to understand market‑specific omnichannel needs and translate them into scalable use cases; act as subject‑matter expert for Omnichannel and ML‑driven engagement solutions across regions
Partner with GDI, Digital, and US Commercial teams to plan and operationalize Omnichannel ML rollouts, ensuring consistency, sustainability, and alignment to global standards
Introduce industry best practices in data science, ML engineering, and MLOps—focusing on omnichannel personalization, customer engagement, and commercial analytics
Qualification
Required
Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and ten (10) years of relevant experience
Master's degree in a relevant quantitative field and eight (8) years of relevant experience
PhD in a relevant quantitative field and two (2) years of relevant experience
Deep expertise in machine learning and applied statistics
Experience working in regulated pharmaceutical commercial environments
Ability to balance innovation with enterprise‑grade execution at scale
Proven ability to design and engineer machine‑learning solutions for next‑best‑action, HCP engagement prediction, customer journey modeling, and omnichannel personalization
Proficiency with modern cloud‑based data and ML platforms (e.g., AWS, Databricks, Azure ML), including scalable data pipelines and model deployment frameworks
Hands‑on experience with containerization and orchestration technologies (e.g., Docker, Kubernetes) to support production‑grade ML workflows
Strong understanding of regulatory and compliance considerations relevant to commercial analytics and ML, including HIPAA, GDPR, FDA guidance, and principles for responsible data use
Fluency in modern ML engineering tooling and languages (e.g., Python, PySpark, MLflow, Airflow, feature store technologies)
Experience operationalizing ML solutions into enterprise ecosystems such as CRM systems, omnichannel orchestration platforms, and customer data platforms (CDPs)
Exceptional written and verbal communication skills, with the ability to translate complex technical concepts into clear narratives tailored for senior business stakeholders
Demonstrated experience leading and influencing senior‑level stakeholders in a matrixed organization, driving alignment across technical and commercial functions
Proven ability to deliver complex, multi‑stakeholder programs with measurable business impact, from concept through production deployment
Strong capability to evaluate, pressure‑test, and pilot external technologies and vendor solutions relevant to omnichannel engagement, machine learning engineering, and commercial analytics
Preferred
Bachelor's degree with 10+ years, Master's degree with 8+ years, or PhD with 6+ years of experience in data science, machine learning engineering, analytics, computer science, or related quantitative fields
Proven experience developing, deploying, and scaling machine‑learning solutions in commercial or omnichannel environments (e.g., next‑best‑action, personalization models, engagement prediction)
Demonstrated success operationalizing ML solutions from pilot to production, including data pipeline design, MLOps, model monitoring, and performance optimization
Experience collaborating with measurement, insights, and commercial analytics teams to integrate validation feedback and refine ML‑driven recommendations
Deep understanding of omnichannel data structures (HCP engagement, CRM, digital behaviors) and familiarity with pharmaceutical commercial processes and compliance considerations
Ability to influence cross‑functional partners, drive alignment, and lead enterprise‑scale technical initiatives in a matrixed organization
Benefits
Discretionary annual bonus
Discretionary stock-based long-term incentives (eligibility may vary based on role)
Paid time off
Company-sponsored medical, dental, vision, and life insurance plans
Company
Gilead Sciences
Gilead Sciences is a biopharmaceutical company that discovers, develops, manufactures and commercializes therapies for critical diseases.
10001+ employees
H1B Sponsorship
Gilead Sciences has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (269)
2024 (241)
2023 (222)
2022 (208)
2021 (235)
2020 (187)
Funding
Current Stage
Public CompanyTotal Funding
$4.41BKey Investors
Abingworth
2024-11-13Post Ipo Debt· $3.5M
2024-02-29Post Ipo Equity· $210M
2023-09-07Post Ipo Debt· $2B
Leadership Team
Keeley Wettan
Senior Vice President, Legal
Patrick Loerch
Senior Vice President, Clinical Data Science
Recent News
2026-02-06
Longevity.Technology
2026-02-06
Genetic Engineering News
2026-02-05
Company data provided by crunchbase