Data Science Manager

• • 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.