Biogen's Decision & Quality Analytics Innovation (DQAI) team is seeking an experienced Data Scientist to lead the generation of actionable insights within the team, applying advanced analytics to derive meaningful insights that inform decision-making across Portfolio Leadership, Analytics, & Insights (PLAI) and Project & Portfolio Management. The role requires translating complex data into narratives that drive operational and strategic outcomes, supporting the development of analytic frameworks and methodologies, and playing a key role in cross-functional collaboration and capability building.
Requirements
- Proven expertise in Python and SQL/R, with experience applying statistical, ML, and visualization techniques in production-grade environments.
- Strong competency in software development or data engineering (e.g., version control, modular code design, APIs, pipelines), enabling deployment across a broad range of analytics and operational projects.
- Familiarity with FAIR data principles and modern data engineering stacks (e.g., Snowflake, Databricks).
- Enthusiastic AI advocate who leverages emerging tools to enhance productivity, accelerate insight generation, and scale analytical impact.
- Requires 5–7 years of experience in data science, analytics, or a comparable domain, including insight generation within pharmaceutical R&D or portfolio analytics.
- Recognized for independent problem solving, innovative thinking, and the ability to integrate best practices with hands-on execution in a fast-paced, highly regulated environment.
Responsibilities
- Champion the use of modern AI assistants (e.g., Azure OpenAI, Copilot, GenAI-powered BI) to accelerate data exploration, automate workflows, and enhance storytelling of insights.
- Lead the design and delivery of data-driven insights that shape strategic and operational decision-making across PLAI, and Project & Portfolio Management.
- Analyze complex, multi-source data to identify trends, risks, gaps, and opportunities in the pharmaceutical R&D portfolio.
- Translate ambiguous business questions into well-structured analytical problems and convert results into actionable recommendations.
- Apply advanced statistical modeling and machine learning to uncover root causes, predictive indicators, and optimization opportunities.
- Scope, prioritize, and deliver high-impact analytics projects that balance innovation with manageable risks and resource requirements.
- Collaborate with data engineering and governance teams to ensure data readiness, integrity, and scalability for advanced analytics.
Other
- BA or MS in Data Science, Computer Science, Information Systems, or a related field required; advanced/graduate degree strongly preferred.
- Effective communicator, skilled at explaining complex or sensitive information and building consensus across technical and non-technical stakeholders.
- Work independently with minimal guidance, exercising sound judgment to solve complex problems and provide new perspectives on existing approaches.
- Act as a resource and mentor for colleagues with less experience; lead small projects or project components within broader initiatives.
- Deliver clear insight summaries, reports, and presentations that highlight implications and recommendations for senior decision-makers; explain difficult or technical results to non technical stakeholders.
