Define and execute data science solutions end-to-end, from problem framing through production deployment.
Build machine learning models (classification, regression, clustering, ranking) for advertiser segmentation, propensity modeling, and recommendations.
Apply causal inference and experimentation methods (A/B testing, difference-in-differences, propensity score matching) to measure the impact of marketing interventions.
Analyze large-scale advertiser behavioral data to identify trends, surface growth opportunities, and support optimal decision making.
Collaborate with colleagues across science and engineering disciplines for fast turnaround proof-of-concept prototyping at scale.
Establish and drive data hygiene best practices to ensure coherence and integrity of data feeding into production ML/AI solutions.
Leverage GenAI and LLM capabilities to enhance science products where applicable
A day in the life
You will solve real-world problems by analyzing large volumes of advertiser data, building predictive models, designing experiments, and measuring business impact. You will prototype rapidly, validate ideas with data, and partner with engineers to productize and scale successful solutions. You will collaborate daily with scientists, engineers, and product managers across the advertising organization, working in a cross-functional, fast-paced environment where data drives decisions and helps advertisers grow.
About the team
We are a team of Applied Scientists, Research Scientists, Data Scientists, and Business Intelligence Engineers with deep expertise in ML, NLP, Gen-AI, RL, and causal inference, from a diverse range of backgrounds. We partner closely with strong engineers, product managers, and sales leaders who bring ads-industry depth and experience building scalable modeling and software solutions.
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
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
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, NY, New York - 153,400.00 - 207,500.00 USD annually
