Fraud Analyst

Job Description

Job Description

We are looking for an experienced Business Analyst to join our team in San Francisco, California. In this long-term contract role, you will play a critical part in identifying and mitigating fraud risks while ensuring a seamless customer experience. If you are skilled in fraud analytics, data analysis, and cross-functional collaboration, this opportunity will allow you to make a meaningful impact in a dynamic and fast-paced environment. This position is hybrid with 2 days onsite required.

Responsibilities :

• Monitor and analyze fraud metrics to identify trends and emerging risks.
• Conduct in-depth investigations on flagged accounts and transactions to validate legitimate customers and reduce friction.
• Develop and maintain dashboards and reports to track fraud KPIs using tools like Snowflake and Tableau.
• Collaborate with cross-functional teams to identify gaps in payment and sign-up processes.
• Provide actionable recommendations to reduce fraud losses and enhance detection accuracy.
• Partner with stakeholders to refine fraud detection policies and workflows.
• Translate data insights into strategic recommendations for business leaders.
• Contribute to the development of scalable fraud prevention strategies while addressing immediate challenges.
• Work closely with engineering and product teams to implement fraud solutions.
• Stay informed about evolving fraud trends to proactively address potential vulnerabilities.
• Minimum of 5 years of experience in fraud and risk analysis within SaaS, eCommerce, or FinTech industries.
• Strong expertise in digital fraud prevention, payments risk, chargebacks, and account abuse.
• Advanced proficiency in querying and analyzing large datasets using tools like Snowflake and Tableau.
• Demonstrated ability to conduct detailed investigations and provide strategic insights.
• Excellent communication skills, with a talent for presenting data-driven findings to senior leadership.
• Familiarity with SQL and Snowflake is a plus.
• Understanding of machine learning in the context and appllication of fraud.
• Self-starter with the ability to manage workflows and deliver results independently.
• Proven experience in collaborating with cross-functional teams to implement fraud prevention strategies.