Data Scientist III

Job Title: Data Scientist III
Location: Cambridge, MA 02142 (Hybrid - 3 Days Onsite)
Duration: 06 Months
Job Description:
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.
Key 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.
• pply 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 (Client, 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:
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.