HOW MIGHT YOU DEFY IMAGINATION?

If you feel like you’re part of something bigger, it’s because you are. At Amgen, our shared mission—to serve patients—drives all that we do. It is key to our becoming one of the world’s leading biotechnology companies. We are global collaborators who achieve together—researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide. It’s time for a career you can be proud of.

Live | What you will do

As the Therapeutic Area (TA) Decision Sciences Lead, you will be the single point of accountability for all data science and measurement work supporting your assigned TA(s). You will work closely with U.S. CD&A Decision Sciences teams to design, deliver, and operationalize models and insights that support TA-specific business needs.

Key Responsibilities

• Lead end-to-end delivery of patient analytics, including patient journey insights, cohort definitions, segmentation, adherence/persistence, and early-signal analyses.

• Drive the development of predictive models such as patient triggers, HCP alerts, identification models, and risk-based prediction frameworks.

• Oversee analytical methodologies for model measurement, including performance evaluation, causal inference, lift analysis, and test design for model validation.

• Ensure all modeling and measurement work follows Amgen’s standards for scientific rigor, documentation, reproducibility, and governance.

• Partner with U.S. Decision Sciences leaders to define analytical priorities, refine problem statements, and ensure TA alignment.

• Collaborate with engineering/platform teams to operationalize models, including model deployment, monitoring, drift detection, and retraining strategies.

• Review and synthesize model outputs and analytical results into structured, actionable insights for TA stakeholders.

• Mentor and guide L5/L4 data scientists supporting the TA on modeling methods, measurement frameworks, and analytic best practices.

Thrive | What you can expect

Amgen invests in your professional growth through continuous learning, leadership development, and opportunities to apply advanced analytics to meaningful patient and commercial challenges.

Basic Qualifications

• Master’s or PhD in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related quantitative field.

• 12+ years of experience in data science or advanced analytics, ideally in pharmaceutical or life sciences analytics environments.

• Experience working with real-world data such as claims, EMR, specialty pharmacy, or other longitudinal datasets.

• Strong hands-on or oversight experience in predictive modeling, machine learning, and/or causal inference.

• Proficiency with Python, SQL, Databricks, and familiarity with MLflow (for model lifecycle review and guidance).

• Demonstrated ability to clearly translate complex analytical work into actionable insights for non-technical partners.

• Experience leading analytics delivery and coaching junior data scientists.

Preferred Qualifications

• Experience building alert/trigger models, patient-finding models, and next-best-action frameworks.

• Exposure to designing experiments or measurement frameworks (e.g., uplift modeling, holdouts, causal impact).

• Familiarity with cloud-based ML deployment, feature stores, or production ML practices.

• Strong communication, structured storytelling, and influence skills.