Associate Director, Marketing Sciences

Gilead Sciences • Parsippany, NJ

1d

About The Position

At Gilead our pursuit of a healthier world for all people has yielded a cure for hepatitis C, revolutionary improvements in HIV treatment and prevention as well as advancements in therapies for viral and inflammatory diseases and certain cancers. We set and achieve bold ambitions in our fight against the world’s most devastating diseases, united in our commitment to confronting the largest public health challenges of our day and improving the lives of patients for generations to come. Associate Director, Marketing Sciences at Gilead leads the design, development, and scaling of advanced omnichannel machine learning (ML) capabilities to enhance data‑informed commercial decision making. The role focuses on modeling HCP engagement patterns, understanding sales and patient‑journey dynamics, translating complex commercial questions into rigorous analytical solutions, and delivering measurable impact across brand, sales, and omnichannel initiatives. This position partners closely with cross‑functional stakeholders across Marketing, Commercial Operations, Product Management, Data Engineering, and Digital teams to build reproducible, scalable machine learning products. Responsibilities include developing and maintaining predictive models, next‑best‑action algorithms, content processing frameworks, and experimentation methodologies; operationalizing these solutions into production environments; and ensuring ongoing model performance and governance while partnering with the measurement team to integrate their insights and feedback into our solutions across markets and therapeutic areas. The Associate Director is also expected to provide scientific and technical leadership—shaping omnichannel machine learning strategy, and influencing senior stakeholders through clear storytelling and actionable recommendations. Success in the role requires deep expertise in machine learning and applied statistics, experience working in regulated pharmaceutical commercial environments, and the ability to balance innovation with enterprise‑grade execution at scale.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and ten (10) years of relevant experience OR Master’s degree in a relevant quantitative field and eight (8) years of relevant experience OR PhD in a relevant quantitative field and two (2) years of relevant experience
• Deep expertise working with pharmaceutical commercial datasets, including IQVIA Xponent, DDD, NPA, medical & pharmacy claims, formulary/coverage data, and HCP reference data; experienced in integrating digital engagement signals (email, web, CRM, field activity) for omnichannel modeling.
• 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).
• Recognized as a trusted machine learning engineer to Commercial, Marketing, Digital, and cross‑functional teams, with the ability to influence omnichannel strategy through machine learning algorithms and data‑driven recommendations.
• 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.
• Structured Problem Solving - Demonstrates the ability to bring clarity to complex challenges by applying structured thinking, guiding teams throughambiguity, and mobilizing resources to deliver timely and effective solutions.
• Collaborative Influence - Influences without direct authority by building trust, demonstrating subject matter expertise, and communicating withauthenticity. Listens actively, adapts messaging to the audience, and uses data-driven persuasion to align stakeholders.
• Results Orientation - Maintains a strong focus on outcomes, consistently driving toward ambitious goals—even in the face of adversity. Takes ownership, makes informed decisions, and ensures accountability to move initiatives forward.
• Strategic - Anticipates evolving business needs and market dynamics. Translates vision into actionable plans, identifies growth opportunities, and adjusts priorities to align with long-term objectives.
• Measurement-Driven - Champions a culture of evidence-based decision-making. Designs and executes strategies with measurable impact, leveraging KPIs and analytics to track performance and optimize results.
• Enterprise Thinking – Advocates for decisions and actions that foster cross-functional collaboration and breaking down silos to drive unified outcomes. Encourages a big-picture perspective, long-term value creation, and a unified approach to business challenges, ensuring that decisions promote the overall health and success of the organization.
• Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams.
• Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current performance and future potential. They ensure employees receive feedback and insight needed to grow, develop and realize their purpose.
• Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem.

Nice To Haves

• 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.
• Strong ability to translate complex technical concepts into clear, business‑focused narratives tailored for senior commercial stakeholders.
• 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.

Responsibilities

• Omnichannel Machine Learning Strategy & Solution Development 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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Director