**W2 ONLY**
Overview:
The Senior Manager, Data Science will be a key contributor to our U.S. Data Science team, developing advanced analytic solutions that drive strategic initiatives across Marketing, Sales, Access, and Digital.
This role is ideal for a hands-on Data Scientist who thrives at the intersection of analytics, commercial strategy, and healthcare innovation-someone who can build robust models, translate data into action, and collaborate with cross-functional partners to influence decisions.
You’ll design and deploy marketing mix models, develop predictive and patient-level analytics, measure digital ROI, and apply generative AI to commercial challenges - all while working with unique biopharma datasets and within a compliance-driven environment.
Ideal Candidate Profile
- You are a commercially minded Data Scientist who can model complex patient and HCP journeys, optimize multi-channel investments, and measure both short- and long-term marketing impact.
- You’ve built MMM models, run predictive analytics, deployed Next Best Action (NBA) frameworks, and translated digital performance data into ROI-driven decisions.
- You’re fluent in pharma datasets, comfortable productionizing models, and curious about applying GenAI and NLP to accelerate insights.
- You blend technical mastery, business acumen, and communication skills to influence senior stakeholders.
Responsibilities
Advanced Analytics & Predictive Modeling
- Independently design, build, and deploy predictive models for HCP targeting, patient initiation/adherence, sales forecasting, and resource allocation.
- Lead Next Best Action (NBA) strategy development to improve HCP engagement, field force productivity, and tailored omnichannel experiences.
- Develop and productionize Patient 360 models and lead generation algorithms using patient-level, market, and specialty pharmacy data.
- Apply machine learning, NLP, and large language models (LLMs) to extract insights from unstructured data (e.g., field notes, CRM interactions, coaching reports).
Marketing Mix, Digital ROI & Commercial Measurement
- Build and maintain marketing mix models (MMM) and budget optimization tools to inform multi-channel spend decisions.
- Conduct scenario planning and ROI analyses for DTC, HCP, field, event, and digital investments.
- Integrate digital analytics (media impressions, engagement, conversion) with offline datasets for a unified measurement of marketing effectiveness.
- Design attribution frameworks that account for long and complex patient/HCP decision cycles.
Experimentation & Optimization
- Design and execute A/B tests, geo-lift studies, and holdouts to validate campaign impact.
- Collaborate with digital teams to implement tagging/tracking strategies for accurate cross-channel measurement.
- Leverage advanced analytics for budget reallocation simulations to maximize commercial ROI.
Data Integration & Compliance
- Ingest, harmonize, and analyze large-scale datasets from APLD, PlanTrak, claims, EMR/EHR, specialty pharmacy, CRM, and syndicated data sources (IQVIA, Symphony, Komodo, Veeva).
- Ensure all data handling complies with HIPAA, GDPR, and internal governance policies.
Collaboration & Communication
- Partner with Marketing, Sales, Access, IT, and external vendors to develop and deploy analytics solutions in production.
- Translate technical outputs into clear, actionable insights for executive decision-making.
- Mentor junior analysts and data scientists, fostering a culture of analytics excellence.
- Present findings at leadership forums and contribute to external publications or conferences where appropriate.
Qualifications
Required:
- Master’s degree (or higher) in Data Science, Statistics, Applied Mathematics, Computer Science, Business Analytics, or related field.
- 5 – 7 years of hands-on experience in data science or advanced analytics, preferably in pharmaceutical, biotech, or healthcare.
- Strong knowledge of supervised/unsupervised learning, regression, clustering, A/B testing, and optimization.
- Proficiency in Python, R, SQL and experience with data platforms such as Snowflake.
- Expertise in MMM tools, predictive modeling, and digital ROI measurement.
- Familiarity with commercial data sources: APLD, PlanTrak, specialty pharmacy, claims datasets.
- Strong communication skills with the ability to simplify complex analytics for non-technical audiences.
Preferred:
- Experience applying generative AI and NLP in commercial analytics.
- Familiarity with patient journey analytics, launch planning, and omnichannel strategy.
- Experience with visualization tools like Tableau, Power BI, or Looker.
Soft Skills
- Strong business acumen with an understanding of marketing, sales, and market access levers in biotech/pharma.
- Strategic thinker who can also roll up sleeves for hands-on coding and model development.
- Collaborative and adaptable in a fast-paced, high-stakes environment.
- Continuous learner with curiosity for emerging technologies and methods.