Associate Director, Data Science Lead

This job is with Biogen, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

About This Role
The Associate Director, Data Science Lead, will play a pivotal role in Biogen's Data Science team, driving the development of advanced modeling solutions that inform strategic business decisions across Marketing, Sales, and Access. This role will be responsible for leading high-impact data science initiatives including marketing optimization, patient-level predictive analytics, machine learning-based personalization, and field force effectiveness strategies.
As a hands-on contributor, you will guide and execute while collaborating with cross-functional teams to ensure that data science outputs are actionable, accurate, scalable, and aligned with brand priorities. You'll be a thought partner to commercial leadership, championing the use of data and AI to deliver measurable business value.
What You'll Do:
Execute flawlessly the long-term data science and AI vision, ensuring alignment with enterprise capability roadmaps, commercial priorities, and emerging AI/ML trends.
Lead 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 and extract insights from unstructured data.
Act as a trusted partner to the insights and marketing teams, demonstrating rigor and knowledge in data science algorithms, while displaying agile ways of working, accountability and value.
Being open to feedback from adopters on the quality of outputs and building 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 that drive measurable impact across marketing, sales, and access strategies.
Guide business stakeholders through insight interpretation and activation, ensuring outputs are integrated into workflows and decision-making processes.
Provide technical expertise and thought leadership on the development of analytical tools, reusable frameworks, proprietary data products, and service lines-contributing directly where needed.
Promote analytical rigor, responsible experimentation, and model governance best practices, serving as a champion of quality and innovation across the analytics organization.
Collaborate with a high-performing team of data scientists, that encourages learning and experimentation.
Collaborate with IT to develop and co-create the ML Ops environments and deliver productized solutions
Design and operationalize Next Best Action (NBA) strategies using machine learning to optimize field force effectiveness, drive personalized omnichannel engagement, and increase HCP engagement ROI.
Develop and scale Patient 360 models and predictive targeting algorithms to support AI-driven lead generation, enable high-value patient outreach, and enhance commercial performance across key therapeutic areas.
Guide measurement and ROI optimization efforts through marketing/media mix modeling and budget allocation using data from APLD, Plan Trak, claims, and specialty pharmacy sources.
Manage relationships with external analytics partners, ensuring alignment with internal data engineering, insights, IT, and compliance teams for scalable, secure solution delivery.
Who You Are:
You are a data scientist with strong business instincts, a leadership presence, and a passion for solving ambiguous problems. You thrive at the intersection of analytics and action-building machine learning pipelines that scale and deliver insights that drive strategic decisions. You're not only a strong individual contributor but also an experienced team leader who enjoys guiding others with ideas, mentoring talent, and fostering collaborative problem solving.
Experience

Required:

Minimum 7 years of hands-on analytics or data science experience, including at least minimum 4 years leading data science projects or teams.
Strong command of statistical modeling supervised and unsupervised learning, A/B testing, and time-series forecasting.
Strong experience in marketing mix, portfolio optimization, decision engine build Gen AI product design
Experience deploying data science solutions in a commercial setting-ideally within pharma, biotech, or healthcare.
Proficient in Python, R, SQL, and Snowflake; experience with Power BI, Tableau, or other data visualization tools.
Proven track record of designing and implementing Next Best Action strategies, marketing optimization models, and omnichannel analytics.
Experience working with APLD, Plan Trak, specialty pharmacy, or claims datasets.
Strong communication and influencing skills; comfortable presenting to senior stakeholders and cross-functional teams.
Preferred:
Master's degree in data science, Statistics,…