BASIC REQUIRED SKILLS:

• Demonstrated experience in organizing, analyzing, and interpreting data for predictive and operational insights.
• Knowledge and expertise in facilitation techniques, data integration, and IDEF methodologies.
• Experience designing and managing analytic studies.
• Familiarity with AI/ML development and deployment environments (e.g., Databricks).
• Experience with technical reporting and stakeholder communication.
• Ability to work independently and collaboratively on data science projects.

OTHER DESIRED SKILLS:

• Experience using Git for version control in team settings
• Background in regulated environments such as FDA or similar public health agencies
• Ability to contribute to cross-functional teams implementing AI and ML capabilities
• Familiarity with cloud-based development environments

EDUCATION:

• Bachelor’s or Master’s degree in a relevant field
  Job Type: Full-time
  Pay: $123,367.59 - $138,571.73 per year

Benefits:

• 401(k)
• Dental insurance
• Health insurance
• Paid time off
• Vision insurance

Work Location: Remot

• Oversee the collection, storage, categorization, and interpretation of data to support pharmaceutical quality surveillance efforts.
• Sift through data points, analyze business results, and develop organized outputs to inform predictive insights and business proposals.
• Compare findings to current agency processes to identify optimization opportunities.
• Set up and manage new studies that inform the development of surveillance models and related systems.
• Research, develop, test, and deploy modern approaches to surveillance modeling and data science automation.
• Support the development of SSM (Site Selection Model) and other quality surveillance automation efforts in a cloud environment.
  · Support the maintenance and development of AI/ML models and technologies in Databricks.

· Provide project management documentation and support for assigned data science efforts.

• Collaborate with OQS Subject Matter Experts to evaluate and implement additional data science, AI, and machine learning systems.
• Use version control tools (e.g., Git) in a collaborative, team-based environment to contribute to the development of advanced analytics solutions.
• Prepare and deliver technical reports and presentations summarizing modeling findings and system outputs.
• Participate in weekly progress meetings and submit monthly progress reports to the Supervisor and Program Lead.
• Complete all required trainings by the established deadlines and maintain training records as required.