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.
