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Salary
$22k – $55k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Amgen is an American biotechnology company founded in Thousand Oaks in 1980 that became one of the first firms to turn recombinant protein research into large commercial medicines. Its history rests on Epogen and Neupogen, and its current portfolio spans bone health with Prolia and Evenity, inflammation with Otezla and Tezspire, cardiovascular disease with Repatha, oncology including the bispecific antibody Blincyto, and a biosimilars business built on its own manufacturing capacity. The company is listed on Nasdaq, is a component of the Dow Jones Industrial Average, and expanded further into rare disease through its acquisition of Horizon Therapeutics.

Career Category

Information Systems

Job Description

Data Scientist (Patient Finding)

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.

Role Overview

This role will work closely with a Senior Data Scientist to support patient finding initiatives across Amgen’s Rare Disease Business Unit (RDBU). The candidate will contribute to analytics and modeling efforts spanning multiple stages of the patient journey, helping identify patients earlier and enable timely intervention.

Live | What you will do

  • Support analytics and predictive modeling projects across commercial data science use cases
  • Assist in data preparation, exploratory analysis, feature engineering, and performance tracking
  • Contribute to development of predictive models under guidance of senior data scientists
  • Support patient finding use cases across the patient journey (e.g., pre-diagnosis signals, diagnosis, treatment triggers, relapse indicators)
  • Assist in generating actionable insights and summaries for business stakeholders
  • Maintain and operationalize code assets, dashboards, and data pipelines in Python/SQL environments
  • Follow best practices for documentation, version control, and reproducibility
  • Collaborate with cross-functional teams and participate in stakeholder discussions alongside L5 leads
  • Continuously learn and apply methods such as predictive modeling, experimentation, and causal inference

Thrive | What you can expect

As we work to develop treatments that take care of others, we also work to care for our teammates’ professional and personal growth and well-being.

  • Exposure to end-to-end data science delivery in a commercial pharma setting
  • Opportunity to work on rare disease patient finding and patient journey analytics
  • Mentorship from experienced data scientists and exposure to advanced modeling techniques
  • A collaborative environment focused on learning, impact, and growth

Basic Qualifications

  • Bachelor’s or Master’s in Data Science, Engineering, Statistics, or a related quantitative field
  • 3-5 years of experience in analytics, modeling, or data science delivery
  • Working knowledge of Python and SQL; experience with modern data platforms
  • Experience with data analysis, visualization, and performance tracking
  • Strong attention to detail and focus on high-quality, reproducible work

Preferred Qualifications

  • Exposure to predictive modeling, machine learning, or experimentation frameworks
  • Basic understanding of healthcare data or patient journey analytics
  • Familiarity with patient finding concepts (e.g., early signals, triggers, segmentation) is a plus
  • Interest in rare disease analytics and low-signal data environments
  • Experience with tools such as MLflow, Git, or notebook-based development environments
  • Strong problem-solving skills and ability to work with ambiguous requirements
  • Demonstrated ability to collaborate effectively with technical and business teams
.
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