*** 1 year Fixed-Term Contract ***

As a Risk Analyst, you will join a team of talented and dedicated fraud experts who play a pivotal role in fighting fraud and helping our customers succeed. Your work will make a big impact in advancing payment risk decisioning to the next level. The right candidate is an experienced fraud fighter with a love for learning, problem solving, and not afraid of a challenge. They enjoy being part of a close knit team and working on multiple projects simultaneously without compromising quality. 

Here’s more of what you will get to do: 

• Perform proactive risk analysis to identify risk factors and trends of potentially fraudulent activity on large datasets
• Identify fraud trends, document and communicate findings, and lead in the development and implementation of new fraud prevention strategies
• Support Risk Operations with process and tool improvements
• Assist our internal teams by leading fraud and tool insights conversations with potential and existing merchants    

• Turn analysis into actionable insights for fraud mitigation initiatives, ad-hoc reports and presentations

• Assist in special projects and ad-hoc assignments, upon request
• Develop and maintain strong relationships with internal teams and external business partners

Required skills that will allow you to thrive in this role:

• 5+ years experience in e-commerce, payments or risk-related industry with either traditional and non-traditional payment methods.
• Strong understanding of ecommerce payments landscape
• Strong analytical skills and an understanding of how to utilize data to target improvements and solve problems
• Experience with database language (e.g., SQL) as well as BI and reporting tools (Looker, Tableau, Splunk, etc.)
• Strong critical thinking skills with advanced judgment capability 
• Ability to manage multiple assignments while working independently 
• Strong communication skills with internal and external stakeholders
• Flexibility to work weekends and holidays

Desirable Skills: 

• Experience in large scale data analysis, tools, and processes. (e.g. Python, R)
• Experience with translating fraud trends into rule logic and/or feature suggestions