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Fraud Risk Data Analyst en Current Openings

Current Openings · New York, Estados Unidos De América · Hybrid

$124,000.00  -  $155,000.00

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About the role

As a Fraud Data Analyst at Rippling, you will play a key role in safeguarding the financial integrity of our clients by identifying and mitigating fraud risks across our suite of financial products. Rippling's Fraud Risk team is looking for a Fraud Risk Data Analyst to help protect the company and its customers from fraud. We're looking for a driven and strategic thinker to focus on our new customer onboarding and fraud detection processes. In this role, you'll be instrumental in developing strategies that block bad actors from the Rippling platform while preserving a seamless experience for legitimate businesses. This is an excellent opportunity to leverage your skills in data analytics to drive strategic and impactful results, grow your career in a fast-paced, dynamic environment.

What you will do

  • Develop and maintain fraud detection rules and models tailored to the onboarding workflow to detect and block bad actors, continuously refining them to address emerging fraud risks
  • Work closely with the Fraud, Security, Sales, Customer Experience, and Compliance teams to improve fraud onboarding and detection processes and roll out new product risk controls
  • Identify suspicious activities and fraud patterns, and perform thorough investigations on high-risk bad actors when necessary. Leverage data analysis and fraud detection tools to make informed decisions.
  • Utilize SQL to regularly assess fraud risk across new customers, recommending and implementing strategies to minimize risk and improve fraud prevention effectiveness.
  • Monitor key performance indicators (KPIs) and provide regular reports on fraud losses, false positive rates, and team efficiency to senior management

What you will need

  • 2+ years of experience as a data analyst in a fraud, risk, or security function, with a focus on customer onboarding or underwriting.
  • Strong SQL skills with the ability to write complex queries to analyze large datasets, identify trends, and generate fraud-related reports. Experience with SQL-based tools (e.g., MySQL, PostgreSQL, or similar databases) is essential.
  • Experience with business intelligence tools like Tableau, Looker, or similar.
  • Effective communication and presentation skills, capable of articulating complex data and risk insights to various stakeholders.

Nice to Have

  • In-depth understanding of payments risks and funds flows, specifically within ACH and bank transfer fraud, account takeovers, wallet and corporate card transaction fraud
  • Experience in SaaS or FinTech environments: Prior experience working in a fast-paced, tech-driven environment with a focus on financial services or SaaS is beneficial.

Additional Information

Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email [email protected]


Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a defined radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.



This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here.


A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location. Final offer amounts may vary from the amounts listed below.


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