Data Scientist (Patient Finding)
At a glance
Mid-level Data Science role at Amgen. Hyderabad · full-time.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Prepare data, explore patterns and build features for commercial analytics and predictive modeling work
- Help develop predictive models with senior data scientists guiding the work
- Analyze patient journey signals, including pre-diagnosis, treatment triggers and relapse indicators
- Maintain Python and SQL code, dashboards and data pipelines, with documentation and reproducible practices
- Turn findings into stakeholder summaries and join cross-functional discussions with senior leads
What you bring
- A bachelor’s or master’s degree in data science, engineering, statistics or another related quantitative field
- Three to five years delivering analytics, modeling or data science work
- Working ability in Python and SQL, plus experience using modern data platforms
- Experience analyzing and visualizing data and tracking performance
Who this fits
This mid-level role suits someone who can contribute to modeling while learning from senior data scientists. You’ll work on rare disease patient-finding and patient-journey analytics, alongside technical and business teams.
From the employer
Career Category
Information SystemsJob 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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