Sr Product Mgr Tech - MBA Catalog Experimentation and Impact Measurement

Do you want to shape Amazons experimentation capabilities in the era of Generative AI As we navigate the rapidly changing landscape of ecommerce particularly with the advent of Generative AI your role will be crucial in shaping how Amazon teams sellers and vendors optimize catalog listings for superior customer experience. Join us on the mission to create best product listings to facilitate wellinformed and fast buying decisions for Amazons customers. We are building feedback loops for Large Language Models and Amazon teams enriching product data through experimentation at Amazon scale.
In this role you will lead the conceptualization delivery and worldwide adoption of Catalog Experimentation Platform (CEP). Through experiments we bring voice of the customer to our business stakeholders. You collaborate with the economists to help users design the experiments correctly and also guide the users on interpreting outcomes which are generated through a statistical analysis. You advocate for decisions in the best interest of our customers even when the outcomes might be unpleasant for the experimenters. Impact measurement techniques often rely on experimentation.
Measurement of the impact of each initiative that intends to improve product data quality is crucial for prioritization decisions and to fine tune each initiatives strategy. You collaborate with the economists to identify and apply the best possible causal inference methodology for each initiative. You have an opportunity to extend the scope of CEP and make it a goto destination in Amazon for impact measurements of Catalog improvement programs.
Finally to make experimentation and impact measurement work at Amazon scale without compromising on the reliability you collaborate with your engineering counterparts to build systems for automation self service mechanisms and guardrails.

Key job responsibilities
1. Work backwards from customer experience to define strategy and build a product roadmap for Catalog Experimentation Platform (CEP). CEP is used to run A/B experiments on Catalog listings.
2. Launch new products/features by partnering with CEP engineering and science teams.
3. Drive adoption by partnering with teams building large language models for the Catalog and business stakeholders across different product categories.
4. Partner with economists and other PMs in the team to develop frameworks and shape the thinking of business stakeholders and leadership on impact measurement methodologies.
4. Represent CEP in Amazon wide forums on experimentation and impact measurements.

A day in the life
Learn about the strengths and challenges of experimentation platforms used industry wide. Develop product strategy (positioning GTM competitive advantage) in collaboration with your engineering and science counterparts.
Track key product metrics communicate wins/misses/learnings to the key stakeholders. Conduct office hours to guide the experimentation users.
Communicate strategy and key updates to org leadership through monthly flashes and business review forums.

About the team
Amazons customers rely on the completeness consistency and correctness of Amazons product data to make wellinformed purchase decisions. Improving the quality of product data is a continuous process. Amazon Selection Catalog Systems (ASCS) is building Catalog Experimentation and Impact Measurement Platform (CEM). CEM enables teams across Amazon to make data driven decisions on what product data changes to simplify and improve the Customers experience. It empowers its users to remove personal bias and let data guide decisionmaking by testing their hypothesis against a representative sample of a broader population. Last but not the least CEM helps LLMs to draw causal inferences between catalog quality improvement actions and customer experience metrics.

fulltime MBA program in mathematics engineering statistics computer science or a related field
Experience working in science technology engineering or mathematics (STEM)
Experience working directly with engineering teams

Familiarity with concepts such as A/B Testing hypothesis testing confidence intervals statistical power type 1 and 2 errors sampling techniques statistical significance randomization

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race national origin gender gender identity sexual orientation protected veteran status disability age 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136100/year in our lowest geographic market up to $235200/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon payments and other forms of compensation may be provided as part of a total compensation package in addition to a full range of medical financial and/or other benefits. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.