Career Category
Information Systems
Job Description
Role Overview
This Data Science Lead will report to the Sr. Data Science Manager and drive patient finding initiatives across Amgen’s RDBU portfolio. The role will work closely with the Data Science Capability Lead to leverage state-of-the-art, innovative frameworks and translate them into scalable solutions that deliver measurable business value.
What you will do
Own patient finding delivery
across brands, spanning key stages of the patient journey (pre-diagnosis, diagnosis, treatment initiation, relapse)
Build
machine learning models and predictive alerts
to identify therapy-appropriate patients earlier and enable timely intervention
Leverage aggregation of patient-level predictions to provider-level signals
to improve field actionability
Align solutions with
brand strategy, field workflows, and commercial priorities
Incorporate insights from
patient support programs, hub, and benefit verification processes
to enhance patient identification
Design and execute
test-and-learn frameworks
(A/B testing, causal inference) to measure business impact
Translate outputs into
clear, decision-ready insights
for cross-functional stakeholders
Partner with global teams to ensure
deployment, integration, and adoption
of models
Continuously improve models based on
real-world performance and data constraints
Basic Qualifications
Master’s degree in Data Science, Statistics, Computer Science, Public Health, or related field
5–7 years of experience in
machine learning, predictive modeling, or healthcare analytics
Strong programming skills in
Python and SQL
Experience with
longitudinal healthcare data
Understanding of
patient journey analytics and experimentation methods
Preferred Qualifications
Experience in
patient finding / patient identification use cases
Familiarity with
hub services, benefit verification, and patient support programs
Experience with
early signal / pre-diagnosis modeling
Understanding of
provider-level targeting and activation
Exposure to
model lifecycle best practices (versioning, monitoring, reproducibility)
Strong ability to
translate analytics into business impact
Why this role matters
This role enables a shift from rules-based identification to
ML-driven patient finding
, helping identify patients earlier and drive meaningful impact on treatment outcomes.
.
