Measurement Science Lead
Notify me about similar jobsAbout this opportunity
Career Category
Engineering
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
.
Job details
How this role compares
Computed from every other active Information Technology role in our database, not just this employer's listings.
We currently track 1167 comparable Information Technology roles across 74 biopharma companies.
Salary context
162 of 1167 peers report a salary range (USD, annualized)
Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.
Where these roles are based
Top locations among the 1167 comparable roles
+ 29 more countries
Seniority mix
667 of 1167 peers have a known seniority level
Therapeutic area mix
2 of 1167 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
Notify me about similar jobs
Get an email when we spot other openings like this one – same job function, comparable seniority, roles you'd actually want to see.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.