Associate Director, Data Science

About the Role

Key Responsibilities

• Define and evolve the long-term data science vision, ensuring alignment with enterprise capability roadmaps, commercial priorities, and emerging AI/ML trends.
• Lead the end-to-end development, deployment, and scaling of data science solutions, including predictive models, clustering, segmentation, optimization, and advanced natural language processing (NLP) and large language models (LLMs), to address complex commercial challenges and extract insights from unstructured data.
• Serve as the primary data science partner for U.S. commercial brand teams, translating business objectives into analytical frameworks that drive measurable impact across marketing, sales, and access strategies.
• Guide business stakeholders through insight interpretation and activation, ensuring outputs are integrated into workflows and decision-making processes.
• Provide technical expertise and thought leadership on the development of analytical tools, reusable frameworks, proprietary data products, and service lines, contributing directly where needed.
• Promote analytical rigor, responsible experimentation, and model governance best practices, serving as a champion of quality and innovation across the analytics organization.
• Build, mentor, and lead a high-performing team of data scientists, fostering a collaborative and innovative environment that encourages learning and experimentation.
• Design and operationalize Next Best Action (NBA) strategies using machine learning to optimize field force effectiveness, drive personalized omnichannel engagement, and increase HCP engagement ROI.
• Develop and scale Patient 360 models and predictive targeting algorithms to support AI-driven lead generation, enable high-value patient outreach, and enhance commercial performance across key therapeutic areas.
• Guide measurement and ROI optimization efforts through marketing/media mix modeling and budget allocation using data from APLD, PlanTrak, claims, and specialty pharmacy sources.
• Manage relationships with external analytics partners, ensuring alignment with internal data engineering, insights, IT, and compliance teams for scalable, secure solution delivery.

Requirements

• 7+ years of hands-on analytics or data science experience, including at least 4+ years leading data science projects or teams.
• Strong command of statistical modeling, supervised and unsupervised learning, A/B testing, and time-series forecasting.
• Experience deploying data science solutions in a commercial setting, ideally within pharma, biotech, or healthcare.
• Proficient in Python, R, SQL, and Snowflake; experience with Power BI, Tableau, or other data visualization tools.
• Proven track record of designing and implementing Next Best Action strategies, marketing optimization models, and omnichannel analytics.
• Experience working with APLD, PlanTrak, specialty pharmacy, or claims datasets.
• Strong communication and influencing skills; comfortable presenting to senior stakeholders and cross-functional teams.

Nice to Have

• Master's degree in data science, Statistics, Engineering, Computer Science, Business Analytics, or related field.

Benefits & Perks

• Base salary range of $158,000 to $217,000, determined through an analytical approach considering skills, experience, location, and internal equity.
• Short-term and long-term incentives, including cash bonuses and equity incentives.
• Comprehensive benefits including Medical, Dental, Vision, & Life insurances.
• Fitness & Wellness programs including a fitness reimbursement.
• Short- and Long-Term Disability insurance.
• Minimum of 15 days of paid vacation plus end-of-year shutdown (Dec 26-Dec 31).
• Up to 12 company-paid holidays plus 3 paid days for Personal Significance.
• 80 hours of sick time per year.
• Paid Maternity and Parental Leave.
• 401(k) with company matching contributions.
• Employee stock purchase plan.
• Tuition reimbursement up to $10,000 annually.
• Participation in Employee Resource Groups.