Sr. Manager, Data Science

About the Role

Key Responsibilities

• Independently build and deploy advanced analytics and machine learning models to drive commercial decision-making-including predictive targeting, segmentation, Next Best Action (NBA), and ROI optimization.
• Translate business challenges into end-to-end data science solutions, collaborating directly with Marketing, Sales, and Access teams to define, develop, and deliver impactful analytics.
• Design and execute NBA strategies to improve HCP engagement, increase field force productivity, and enable tailored omnichannel experiences.
• Develop and productionize Patient 360 models and lead generation algorithms using patient-level and market data to identify high-value outreach opportunities.
• Execute hands-on development of marketing mix models, budget optimization tools, and performance tracking analytics using APLD, PlanTrak, claims, and specialty pharmacy datasets.
• Build and implement NLP and LLM-based applications (e.g., GPT models) to extract insights from unstructured data such as field notes, coaching reports, and CRM interactions.
• Create dashboards, reports, and compelling visualizations to communicate insights to both technical and non-technical audiences across the organization.
• Work directly with internal engineering, IT, and insights partners, as well as external vendors, to develop and deploy analytics solutions in production environments.
• Actively contribute to a high-performance, experimentation-driven data science culture, with a focus on rigor, reproducibility, and continuous learning.

Requirements

• 5-7 years of hands-on experience in analytics or data science, preferably in pharmaceutical, biotech, or healthcare industries.
• Strong knowledge of supervised/unsupervised learning, A/B testing, regression modeling, clustering, and optimization.
• Proficiency in Python, R, SQL, and familiarity with data platforms such as Snowflake; experience with visualization tools like Power BI or Tableau.
• Experience with commercial data sources such as APLD, PlanTrak, specialty pharmacy, and claims datasets.
• Demonstrated experience applying data science to commercial use cases such as NBA, marketing optimization, and HCP targeting.
• Strong communication and collaboration skills with the ability to simplify complex concepts for non-technical audiences.

Nice to Have

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

Benefits & Perks

• Base salary range of $139,000.00-$186,000.00, determined through an analytical approach considering skills, experience, location, and internal equity.
• Eligibility for 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 off for Personal Significance.
• 80 hours of sick time per calendar 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.