Amgen - Data Science Lead - Predictive Analytics
Amgen · Hyderabad
- Experience5–7 yrs
- SalaryNot disclosed
- Work modeonsite
- Levelsenior
- Posted3 Jul 2026
About Amgen
Amgen is hiring in Hyderabad in pharma biotech. This role looks for around 5+ years of experience.
Skills
- Python
- SQL
- Machine Learning
- Predictive Modeling
- Longitudinal Healthcare Data
- Patient Journey Analytics
- A/B Testing
- Causal Inference
The role
A data science lead in a biopharmaceutical company builds machine learning models and predictive alerts from longitudinal healthcare data for patient finding across diagnosis, treatment initiation, and relapse. They aggregate patient-level predictions into provider-level signals, design A/B testing and causal inference frameworks, and translate model outputs into actionable commercial insights. Their defining skills are Python, SQL, and predictive modeling, alongside patient journey analytics, healthcare experimentation, model lifecycle practices, and provider targeting.
Full job description
Role Overview :
This Data Science Lead will report to the Sr. Data Science Manager and drive patient finding initiatives across Amgens 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 :
- Masters 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.
Job Type : Full time.
Note : For your candidature to be considered on this job, you need to apply necessarily on the company's redirected page of this job. Please make sure you apply on the redirected page as well.