Senior Manager, Data Science & AI

Role Summary

The Senior Manager, Data Science Lead will drive the development of advanced modeling solutions that enable automation and decision making for Biogen North America. This role builds high-impact data science solutions including marketing optimization, patient-level predictive analytics, ML-based personalization, and field force effectiveness strategies. You will collaborate with cross-functional teams to ensure outputs are actionable, accurate, scalable, and aligned with brand priorities, and serve as a thought partner to commercial leadership. You will contribute to robust techniques and product design to meet business objectives.

Responsibilities

• Execute flawlessly the long-term data science and AI vision, ensuring alignment with enterprise capability roadmaps, commercial priorities, and emerging AI/ML trends.
• Contribute to 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.
• Act as a trusted partner to the insights and marketing teams, demonstrating rigor and knowledge in data science algorithms.
• Be open to feedback from adopters on the quality of outputs and build corrective model fine-tuning and performance continuously.
• Serve as the primary data science partner for U.S. commercial brand teams, translating business objectives into analytical frameworks.
• Guide business stakeholders through insight interpretation and activation, ensuring outputs are integrated into workflows.
• Provide technical expertise and thought leadership on the development of analytical tools and reusable frameworks.
• Promote analytical rigor, responsible experimentation, and model governance best practices across the analytics organization.
• Collaborate with a high-performing team of data scientists that encourages learning and experimentation.
• Collaborate with IT to develop ML Ops environments and deliver productized solutions.
• Design and operationalize Next Best Action (NBA) strategies using machine learning to optimize field force effectiveness.
• Develop and scale Patient 360 models and predictive targeting algorithms for AI-driven lead generation and patient outreach.
• Guide measurement and ROI optimization efforts through marketing/media mix modeling and budget allocation.
• Manage relationships with external analytics partners, ensuring alignment with internal data engineering and compliance teams.

Qualifications

• Required: Minimum 5 years of hands-on analytics or data science experience, including at least 4 years leading data science projects or teams.
• Required: Bachelor's degree in a quantitative field.
• Required: Strong command of statistical modeling—supervised and unsupervised learning, A/B testing, and time-series forecasting.
• Required: Experience in marketing mix, portfolio optimization, and Gen AI product design.
• Required: Experience deploying data science solutions in a commercial setting, ideally within pharma, biotech, or healthcare.
• Required: Proficient in Python, R, SQL, and Snowflake; experience with Power BI, Tableau, or other data visualization tools.
• Required: Proven track record of designing and implementing Next Best Action strategies, marketing optimization models, and omnichannel analytics.
• Required: Experience working with APLD, PlanTrak, specialty pharmacy, or claims datasets.
• Required: Strong communication and influencing skills; comfortable presenting to senior stakeholders and cross-functional teams.
• Preferred: Master’s degree in data science, Statistics, Engineering