Sr. Fraud Analyst, ABPL Fraud Management

Found in: Talent US C2 - 2 weeks ago


Seattle, United States Amazon.com Services LLC Full time
Interested in driving impact to one of the fastest growing businesses at Amazon and working with one of the largest fraud prevention systems in the world? Amazon Business Payments and Lending (ABPL) is looking for a Sr. Fraud Analyst to manage our loss mitigation strategy for the EU business. The successful candidate will be responsible for developing proactive and reactive fraud management strategies across different payment methods while balancing loss rates and customer experience. The ideal candidate will be comfortable working independently in a fast paced, technical, and high energy environment. They are critical thinkers, analytical, innovative, and resourceful with a history of solving complex and ambiguous problems.

Key job responsibilities
Key responsibilities include:
-Own KPIs that measure fraud management performance and efficiencies.
-Perform end to end evaluation to identify customer friction issues, operational defects, system gaps, and scaling challenges (both system and operational).
-Own and develop policies, processes, and implement them across cross functional teams.
-Contribute to the overall fraud management and product development strategies.
-Present key learnings and vision to stakeholders and leadership.

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

Seattle, WA, USA

BASIC QUALIFICATIONS

- Bachelor’s degree in Risk, Business, Finance, Economics or Equivalent Experience
- Experience in fraud investigations, fraud management, or fraud strategy for e-commerce companies, financial services, or fintech companies.
- Robust analytical and excel skills, including the ability to be hands-on and dive deep into details, identifying root cause and propose solutions
- Hands-on experience of working with data tools/languages such as SQL

PREFERRED QUALIFICATIONS

- Experience in managing fraud across payment methods and cross-border scenarios
- Experience in working with machine learning models or scientists.


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