Measurement Science Lead

Career Category

Job Description

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.

Live | What you will do

• Lead causal inference and impact measurement initiatives to evaluate the effectiveness of commercial and customer engagement strategies.
• Apply advanced statistical methods and experimentation to quantify incremental business impact and inform decision-making.
• Develop attribution frameworks across field and digital customer engagement channels.
• Partner with business teams to translate commercial questions into actionable insights.
• Mentor data scientists and champion best practices in causal analytics and measurement.

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.

You will be part of a collaborative analytics environment where data science is used to improve commercial decision-making, strengthen customer engagement, and help teams better understand patient and HCP needs.

Basic Qualifications

• 5-7 years of experience in causal inference, experimentation, marketing science, or data science.
• Strong expertise in causal inference, statistical modeling, experimental design (A/B testing), and quantifying business impact.
• Experience applying quasi-experimental methods (e.g., propensity score matching, difference-in-differences, synthetic controls, uplift modeling) to evaluate commercial initiatives.
• Proficiency in Python, SQL, and large-scale data environments for experimental analysis and causal measurement.
• Ability to translate complex statistical findings and causal insights into actionable recommendations for business stakeholders.

Preferred Qualifications

• Experience in life sciences, healthcare, or pharmaceutical analytics.
• Experience in commercial analytics