Director, Analytics Standards – Impact Measurement

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop enterprise-wide standards for AI, ML, and data science to be integrated into self-service analytics platforms, ensuring that citizen data scientists adhere to rigorous methodologies automatically.

• Set up model validation protocols, testing frameworks, and quality gates within automated workflows for predictive models and AI solutions.

• Formulate standardized methodologies for common use cases (such as patient predictive models, HCP targeting, and driver analysis) that can be templated for citizen data scientists.

• Establish enterprise-wide frameworks to evaluate analytics impact, including lift analysis, ROI calculation, incrementality measurement, and business value assessment.

• Carry out enterprise-level impact measurement studies to quantify the business value of analytics initiatives and report quarterly and annual ROI to leadership.

• Define production-readiness criteria for AI/ML models derived from self-service platforms, including quality thresholds, documentation requirements, and approval workflows.

• Ensure all outputs related to AI, ML, and data science comply with regulatory standards (such as HIPAA, GDPR, and promotional review) and collaborate with Legal, ERC, and Medical Affairs for governance.

• Oversee outputs from self-service platforms, perform model audits, and offer feedback to platform teams regarding quality enhancements.

⛳️ Requirements

• An advanced degree in Data Science, Machine Learning, Statistics, or a related quantitative discipline; or a bachelor's degree with over 10 years of relevant experience.

• More than 10 years of experience in data science, machine learning, advanced analytics, or AI development.

• At least 5 years of leadership experience in establishing AI/ML standards and measuring impact within the commercial pharmaceutical or healthcare sectors.

• Expert-level knowledge in advanced analytics methodologies, including machine learning, causal inference, experimental design, predictive modeling, and AI validation.

• Extensive understanding of pharmaceutical analytics and the regulatory landscape for AI/ML applications.

• Proficiency in programming for data science/AI and familiarity with AI/ML platforms.

• Demonstrated ability to influence without direct authority and promote the adoption of AI/ML standards across diverse teams.

• Outstanding communication skills, with the capability to convey complex AI/ML concepts to business audiences and executives effectively.

🏝️ Benefits

• Health, life, and disability benefits.

• 401(k) plan with company contribution and matching.

• A variety of additional benefits.

• A generous time-off package that includes vacation, personal days, holidays, and other leave options.