Senior Data Scientist, MAPLE

- 6+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 6+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- 6+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- Strong understanding of statistical concepts, hypothesis testing, and causal learning.
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
- Ability to autonomously lead complex data science projects to completion and drive business impact.
- Experience with developing recommender systems.
- Experience analyzing A/B tests and drawing insights from them.

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 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on 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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking create a huge impact as you help build a state-of-the-art recommendation system? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science through your research!

Key job responsibilities
- Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization.
- Apply supervised and uplift learning techniques to improve ML performance
- Research and implement ML and statistical approaches to add value to the business.
- Design A/B tests and conduct statistical analysis on their results
- Apply machine learning and statistical algorithms to harness enormous volumes of data as we serve our customers
- Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area
- Present science research, contributing to Amazon's science community
- Mentor junior engineers and scientists.

A day in the life
As a Senior Data Scientist in the MAPLE team, your day might start with a stand-up meeting, aligning priorities with your colleagues. You'll then dive into analyzing the results of a recent A/B test on a new recommendation algorithm you've developed. Midday, you might collaborate with engineers to optimize the implementation of your model for production. In the afternoon, you could find yourself mentoring a junior team member on statistical techniques or presenting your latest findings to business stakeholders. You'll also dedicate time to staying current with the latest research in machine learning and recommendation systems, possibly contributing to an internal tech talk or external publication. Throughout the day, you'll be using your expertise to solve complex problems, turning data into actionable insights that enhance the customer experience on Amazon's platform.

About the team
Our team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.