Data Scientist, MAPLE

Are you an experienced data scientist who wants to develop algorithms to help grow Amazon's financial services?

The Amazon Payment Products team needs a Data Scientist to develop the algorithms which power our new marketing tooling which we use to grow our financial services portfolio, driving a measurable P&L impact and creating an amazing customer experience.

Key job responsibilities

• Develop and apply new machine learning algorithms
• Use expertise in supervised and uplift learning algorithms to improve ML performance
• Scale optimization techniques to drive business value
• Design A / B tests and conduct statistical analysis on their results
• Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area
• Present and publish science research, contributing to Amazon's science community
• Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers
• Implement and operate stable, scalable data flow solutions from production systems into end-user facing applications.

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.

We are open to hiring candidates to work out of one of the following locations :

Seattle, WA, USA

BASIC QUALIFICATIONS

4+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical / mathematical software (e.

g. R, SAS, Matlab, etc.) experience

• 3+ years of data scientist experience
• 3+ years of machine learning / statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• 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
• Experience with uplift modeling techniques and / or heterogenous treatment effect estimation
30+ days ago