Associate Data Scientist - Investment Analytics
About this opportunity
Career Category
Engineering
Job Description
Level: Associate (L3)
Role: Marketing Investment Optimization – Investment Analytics
MIO OVERVIEW
The Marketing Investment Optimization (MIO) vertical at Amgen is responsible for enabling data‑driven, decision‑grade marketing investment decisions across brands, channels, and portfolios.
MIO brings together Investment Analytics (IA), Media Analytics (MA), and Marketing Science Operations (MSO) to measure effectiveness, quantify incrementality, and optimize marketing investments.
MIO focuses on marketing mix modelling (MMx), Experimentation and Causal Measurement, Optimization, Media and Campaign analytics, Scenario Planning, ensuring that marketing dollars are allocated to maximize business impact. The team partners closely with Brand Marketing, GCC/Agencies, CD&A, and MSO to translate complex analytics into actionable investment decisions.
Role Summary
The Associate – Investment Analytics role is an entry‑level analytics position within the Investment Analytics team. This role is ideal candidates who are excited about applying analytical thinking, structured problem solving, and data skills to real‑world business questions.
The team will provide structured learning and on‑the‑job exposure. What matters most is curiosity, critical thinking, and a strong learning mindset.
LIVE | WHAT YOU WILL DO
As an Associate, you will work under guidance from Senior Associates and Managers to support analytical deliverables and build strong foundations in applied analytics.
You will:
Develop and apply advanced statistical models that help clients understand dynamic business issues.
Leverage analytic techniques to use data to guide decision-making.
Design custom analyses in R, Python and Excel to investigate and inform business needs.
Assist in preparing analysis summaries, documentation, and presentation materials.
Collaborate with team members to meet project timelines and quality standards and actively communicate project status updates.
Engage in ongoing learning to develop industry knowledge, and technical capabilities.
BASIC QUALIFICATIONS
Bachelor's (3 to 6 Yrs) or master's (2 to 4 Yrs) degree required in any discipline with strong record of academic success in quantitative and analytic coursework such as operations research, applied mathematics, management science, data science, statistics, econometrics or engineering.
Experience in any analytical, data, or problem‑solving role.
Strong SQL skills and hands‑on experience with Python or R.
Preferred Qualifications
Demonstrated ability to perform structured QA and validation.
Experience working with time‑series and investment data.
Exposure to Marketing Mix Modelling (MMx) or econometric analysis.
Experience supporting analytics in pharma, healthcare, or regulated environments.
Strong communication skills with the ability to collaborate closely with Senior Associates to deliver high‑quality analytical outputs.
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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 190 comparable Associate Information Technology roles across 25 biopharma companies.
Salary context
30 of 190 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 190 comparable roles
+ 9 more countries
Seniority mix
190 of 190 peers have a known seniority level
Therapeutic area mix
0 of 190 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.