Data Scientist (Commercial)
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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
Support analytics and predictive modeling projects across Data Science & Measurement and Investment Analytics teams.
Assist in data preparation, exploratory analysis, metric tracking, and performance reporting with high accuracy.
Maintain and operationalize dashboards or reusable code assets in Databricks or Python/SQL environments.
Contribute to project delivery by partnering with senior data scientists and leads on model building, testing, and result summaries.
Drive documentation, version control, and deployment practices using standardized platforms and tools.
Stay curious, continuously learn about methods such as marketing mix modeling, predictive modeling, A/B testing, and causal inference.
Summarize and communicate marketing campaign performance results clearly to stakeholders.
Work in a consultative manner with stakeholders while maintaining deadlines.
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.
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; comfort working in Databricks or similar environments.
Experience with data visualization and performance metric tracking.
Strong attention to detail and a focus on delivering high-quality, reproducible work.
Preferred Qualifications
Critical thinking and structured problem solving ability to intake ambiguous business requirements and develop analytics frameworks
Exposure to marketing mix modeling, predictive modeling, or experiment-based analytics.
Interest in life sciences, healthcare, or pharma analytics environments.
Familiarity with tools such as MLflow, Git, or Jupyter notebooks.
Demonstrated ability to collaborate with analysts, engineers, or business partners to get things done.
Strong ownership of work with a bias towards action
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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 1376 comparable Information Technology roles across 76 biopharma companies.
Salary context
183 of 1376 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 1376 comparable roles
+ 29 more countries
Seniority mix
693 of 1376 peers have a known seniority level
Therapeutic area mix
1 of 1376 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.