Data Sciences Sr Mgr

About the role

Amgen seeks a Data Sciences Sr Mgr to lead therapeutic area decision sciences, overseeing patient analytics, predictive modeling, and model measurement. The role requires 12+ years in data science within pharma or life sciences, expertise in real‑world data, predictive modeling, machine learning, causal inference, and proficiency in Python, SQL, Databricks, and MLflow. Responsibilities include end‑to‑end delivery of patient journey insights, cohort definitions, segmentation, adherence analysis, predictive models, model deployment, monitoring, and translating insights to stakeholders. The manager will mentor junior scientists, collaborate with engineering teams, and ensure scientific rigor and governance. Preferred experience includes alert/trigger models, next‑best‑action frameworks, experimental design, cloud‑based ML deployment, and strong communication skills.

What you’ll do

• 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.

What you’ll bring

• 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.
• Demonstrated ability to clearly translate complex analytical work into actionable insights for non‑technical partners.
• Experience leading analytics delivery and coaching junior data scientists.

Nice to have

• 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.

Skills

Education

Master