Senior Economist

IES Payments is building a first-of-its-kind Economic Profit (EP) framework to measure the
full economic value of Amazon Payment Products (APPs) and payment-led promotional
levers across 9 emerging markets. Today program leaders cannot credibly quantify the total value their products create beyond direct revenue contribution EP changes that.


We are looking for an Economist who will own the incrementality science that underpins
this framework. You will design evolve and defend the econometric methodologies that
measure how payment instruments create value within the transaction (Day-0) and over
the 365-day customer lifetime (DSI). You will be the single-threaded science owner for how
we compute and justify incrementality across always-on instruments promotional constructs weblabs and behavior-change programs.


This is not a support role. You will directly shape how Amazon measures the ROI of its
payment investments across IES and your work will feed into S-Team level planning and
investment decisions.

Key job responsibilities
What Youll Do
Incrementality Methodology Design & Evolve
Own end-to-end design of incrementality computation logic across EP use cases: always-on APPs one-time promotions weblab measurement and ongoing behavior-change programs (e.g. UPI adoption rewards)
Evolve the Day-0 incrementality methodology the novel component that captures value created within the current transaction itself where standard DSI excludes the event day
Design econometric approaches for use cases where GCCP fails (weblabs with instrument dynamics) and where traditional promo measurement breaks down (investment-phase payoff-phase programs)
Develop and validate proxy logic for segment-wise EP cuts in the absence of dedicated compute infrastructure

CBA & Cross-Functional Alignment
Lead the formal methodology defense with CBA V-Team every surrogate every computation every modification to Watsons default workflow requires rigorous scientific justification and CBA sign-off
Align with DEX and Stores Finance on the science behind cost-to-serve incrementality metrics (CoP avoidance UPB savings CoBW reduction)
Navigate the surrogate onboarding challenge: new payment surrogates can cannibalize value currently attributed to existing Marketplace HVAs you will need data-backed arguments to bring Stores leadership on board not just science correctness
Build and maintain the defensibility of EP methodology against internal scientific scrutiny

Partnership with Data Science
Work hand-in-hand with the EP Data Scientist to build a holistic case for payment HVA incrementality you bring the econometric logic they bring the predictive model justification; both must align for CBA acceptance
Jointly defend surrogate onboarding proposals where the economist provides the causal framework and the data scientist provides the feature-level model evidence
Translate econometric findings into business narratives for VP leadership reviews

Geographic Expansion
Adapt and calibrate EP methodology for Brazil Mexico MENA and APAC markets each with distinct instrument mixes data maturity levels and marketplace economics
Determine where the India-built methodology transfers cleanly and where market-specific econometric adaptations are needed

About the team
Our team is dedicated to applying economic thinking to some of Amazons most impactful business questions. We bring together economists with expertise spanning causal inference structural modeling and applied microeconomics to deliver insights that guide long-term strategy. We value intellectual rigor open debate and a collaborative spirit that makes everyone stronger.

We are building toward a future where economic analysis is deeply embedded in decision-making at every level. If you want to work alongside thoughtful curious colleagues and see your work shape how Amazon operates this is the team for you.

- Experience with statistical analytics and programming languages such as R Python Ruby etc.
- Experience in A/B testing
- Experience using data and metrics to influence senior leadership and drive organizational change
- PHd or Masters degree in Economics Econometrics Statistics or a quantitative field with 5 years of industry experience in applied economics or causal inference
- Deep expertise in causal inference methodologies difference-in- differences instrumental variables regression discontinuity synthetic control treatment effect estimation
- Demonstrated experience designing and defending incrementality or attribution measurement frameworks either in tech financial services or marketplace settings.
- Ability to communicate complex econometric concepts to non-technical business and finance leaders
- Comfort with ambiguity this role requires designing methodology for problems where no clean playbook exists

- Experience in analytics and applied economics
- Experience in developing and executing an analytic vision to solve business-relevant problems
- Experience in building statistical models using R Python STATA or a related software
- Experience in industry consulting government or academic research
- PhD in econometrics statistics industrial engineering operations research optimization data mining analytics or equivalent quantitative field
- Experience with customer lifetime value (CLV) or downstream value modeling predicting long-horizon behavioral effects of interventions
- Familiarity with Amazons CBA ecosystem (Dr. Watson DSI/DSE GCCP HVA frameworks) or equivalent internal measurement platforms at other tech companies
- Experience navigating cannibalization and attribution disputes across organizational boundaries situations where your measurement shifts value between teams
- Prior work on payment instrument economics affordability products or fintech ROI measurement
- Experience with large-scale causal inference on transactional data (100M transactions/month)
- Publications or internal whitepapers on applied econometric methodology

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