Pharma R&D Data & AI Strategy Lead

Slalom; Minneapolis (MN); On-site; USD 150,000 - 183,000; Full time

Benefits offered by this job

401(k) with match

Health, dental, & vision coverage

Disability insurance

Well-being reimbursement

Job summary

Slalom is seeking a Pharma R&D Data & AI Strategist to help pharmaceutical and biotechnology clients translate ambitious scientific, business, Data, and AI strategies into measurable R&D outcomes. You will collaborate with senior leaders and multidisciplinary teams to modernize data and AI capabilities across the full R&D lifecycle.

The role spans Research to Clinical Development, enabling scalable data products, governance, and enterprise platforms such as Databricks, Azure, AWS, and Snowflake.

Qualifications

• Significant experience in pharmaceutical, biotechnology, life sciences R&D, or consulting to R&D organizations.
• Strong understanding of pharma R&D lifecycle with depth in Research & Discovery and/or Clinical Development.
• Experience working with Research and/or Clinical data, capable of handling scientific and regulated data.

Responsibilities

• Develop Data & AI strategies for pharmaceutical R&D and translate into actionable roadmaps.
• Partner with R&D executives and scientists to identify high-value Data & AI opportunities.
• Translate strategy into MVPs, data products, backlogs, and governance.

Skills

Pharma R&D experience

Data & AI strategies

Executive communication

Cross-functional collaboration

Education

Life sciences / R&D background

Tools

Databricks

Azure

AWS

Snowflake

Job description

Slalom is seeking a Pharma R&D Data & AI Strategist to help pharmaceutical and biotechnology clients translate ambitious scientific, business, Data, and AI strategies into measurable R&D outcomes. You will collaborate with senior leaders and multidisciplinary teams to modernize data and AI capabilities across the full R&D lifecycle.

The role spans Research to Clinical Development, enabling scalable data products, governance, and enterprise platforms such as Databricks, Azure, AWS, and Snowflake.