Data Science Manager
About this opportunity
Career Category
Engineering
Job Description
Data Science Manager (Commercial) – L5
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 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
6–8 years of experience in causal inference, experimentation, marketing science, commercial analytics, or data science.
Strong expertise in statistical modeling, experimental design, and impact measurement.
Proficiency in Python, SQL, and large-scale analytics environments.
Ability to communicate complex analytical findings to business stakeholders.
Preferred Qualifications
Experience in life sciences, healthcare, or pharmaceutical analytics.
Experience with attribution, incrementality, omnichannel measurement, and marketing effectiveness.
Familiarity with causal ML, uplift modeling, A/B testing, and quasi-experimental methods.
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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 225 comparable Manager Information Technology roles across 30 biopharma companies.
Salary context
42 of 225 peers report a salary range (USD, annualized)
Peers share this role's job function and a matching or adjacent seniority level -- not necessarily the same therapeutic area or country.
Where these roles are based
Top locations among the 225 comparable roles
+ 11 more countries
Seniority mix
225 of 225 peers have a known seniority level
Therapeutic area mix
0 of 225 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
No peers with a known therapeutic area yet.
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.
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.