Amazon is investing heavily in building a world-class advertising business, and we are responsible for defining and delivering a collection of advertising tools and products that drive discovery and Advertiser success. Our products are strategically important to our Retail and Marketplace businesses, driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving with an entrepreneurial spirit and bias for action.
The Marketing Effectiveness & Attribution Science team develops causal inference and machine learning systems to measure the impact of marketing programs across Amazon's advertising ecosystem. We build production-grade attribution models that help business teams understand what's working, optimize resource allocation, and drive advertiser growth. Our work sits at the intersection of econometrics, scalable ML systems, and high-stakes business decisions.
As a Data Scientist on this team, you will own end-to-end modeling pipelines — from problem formulation and experimental design to model development, productionization, and stakeholder communication.
Major responsibilities include:
Translate / Interpret:
Partner with cross-functional teams to translate business questions into rigorous causal inference problems Design observational studies and quasi-experiments to measure marketing effectiveness when traditional A/B tests are infeasible Work with data engineering to instrument new data pipelines when existing data cannot answer the causal question
Measure / Quantify / Expand:
Own and evolve production attribution models across multiple marketing channels Build and maintain causal inference pipelines using methods such as Difference-in-Differences, Synthetic Control, Double Machine Learning, and Media Mix Models Develop scalable PySpark and Python codebases that process large-scale event data Continuously improve model accuracy through feature engineering, heterogeneity analysis, and sensitivity testing
Explore / Enlighten:
Investigate anomalies in model outputs and deep-dive to identify root causes Develop automated data quality checks and model diagnostics Research and prototype next-generation measurement methods
Make Decisions / Recommendations:
Present findings to senior leadership with clear recommendations Build dashboards and self-service tools that enable stakeholders to explore results independently Write production-quality Python code for data analysis, model training, and result publishing
Basic Qualifications
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data scientist experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Bachelor's degree
- Experience applying theoretical models in an applied environment
Preferred Qualifications
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, SEATTLE - 136,000.00 - 184,000.00 USD annually