Top Biotech Data & Analytics Jobs in Madison, WI

Serve as subject-matter expert for Caris assays, clinico-genomic and real-world data to support biopharma partnerships. Design feasibility queries, lead cross-functional RWD research projects, communicate with stakeholders, and support account strategy and product lifecycle activities to advance precision oncology collaborations.

As Commercial Analytics Manager, you'll analyze performance data to develop strategic insights, drive growth, own sales forecasting, and enhance compensation plans in partnership with Finance.

The Senior Director of Biostatistics at Gilead leads data analysis initiatives, directs cross-functional teams, and supports company priorities in statistical analysis and reporting. They ensure effective scientific communication and contribute to strategic departmental initiatives.

The IT Compliance Manager oversees compliance activities, ensuring adherence to regulations like SOX and GDPR, conducting audits, and developing compliance policies.

The Sr. Manager, Biostatistics leads statistical activities for clinical studies, ensuring quality deliverables and compliance with regulatory standards while collaborating cross-functionally and with external partners.

Provide support for data repository and analytics tools in GMP data, focusing on manufacturing and quality domains. Analyze business needs, manage data curation, ensure compliance, and lead documentation and testing efforts.

The Associate Director, Biostatistics supports clinical development programs, ensuring the quality and timeliness of statistical deliverables and collaborating with various teams for effective study designs and data analysis.

The HR Technology BI Developer designs and develops HR analytics platforms to enhance decision-making and improve workforce planning through robust data solutions.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

The Data Engineer will build and maintain data infrastructure, design data pipelines, and develop reusable frameworks, leveraging technologies like Azure Databricks and PySpark for data processing and transformation.