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Fraud Strategy & Analytics Manager

New York, NY

Pay
Pay not listedSimilar roles state $153K–$225K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: SALARIED_FT
From the employer’s posting
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What you’ll work on

Full posting

As a Fraud Strategy & Analytics Manager 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.

  • Develop and own fraud prevention strategies across Payroll, Bill Pay, and Corporate Card

  • Design and tune fraud monitoring and decisioning rules using large transaction datasets

  • Lead complex fraud investigations and root-cause analyses

  • Build dashboards and track fraud losses, detection rates, and false-positive rates

  • Partner with Data Science and Engineering on detection models and risk scoring

From the employer’s posting
As a Fraud Strategy & Analytics Manager 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. You will be responsible for developing and enhancing fraud detection and risk mitigation strategies, with a focus on transaction fraud monitoring, fraud loss prevention, and fraud incident investigation, all while ensuring that decisions are based on robust analytics and large-scale data sets. Using data-driven insights, you will analyze transaction data, identify emerging fraud patterns, and collaborate with cross-functional teams including data science, security, compliance, product, and engineering to implement effective solutions. This is an excellent opportunity to leverage your expertise in data analytics and fraud prevention to drive strategic and impactful results, and grow your career in a fast-paced, dynamic environment. Your responsibilities will include:
Develop and own fraud prevention strategies across Rippling’s financial products, including Payroll, Bill Pay, and Corporate Card
Design, implement, and optimize fraud monitoring and decisioning strategies using large-scale transaction data
Lead complex fraud investigations and root-cause analyses
building dashboards, defining key risk indicators, and monitoring metrics such as fraud losses, detection rates, false-positive rates
Partner with Data Science and Engineering to develop and enhance fraud detection models, risk-scoring methodologies

What you’ll bring

All qualifications

Core experience

  • 5+ years experience in fraud prevention and detection, preferably in the financial technology sector, with a strong focus on payments, lending, and SaaS industries
  • Bachelor's degree in a relevant field (e.g.
  • Strong SQL & Python 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.
  • Familiarity with the fraud investigation tools and industry-leading third-party risk vendors.
  • Experience with fraud detection tools and methodologies is essential.
Qualification wording
5+ years experience in fraud prevention and detection, preferably in the financial technology sector, with a strong focus on payments, lending, and SaaS industries
Bachelor's degree in a relevant field (e.g. Math, Statistics, Operations Research), Master's degree preferred
Strong SQL & Python 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.
Familiarity with the fraud investigation tools and industry-leading third-party risk vendors. Experience with fraud detection tools and methodologies is essential.
Education & alternatives
- 5+ years experience in fraud prevention and detection, preferably in the financial technology sector, with a strong focus on payments, lending, and SaaS industries - Bachelor's degree in a relevant field (e.g. Math, Statistics, Operations Research), Master's degree preferred - Strong SQL & Python 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.

Tools in this posting

  • Python
  • SQL
  • MySQL
  • PostgreSQL
Source — Tool mentions in context
- Bachelor's degree in a relevant field (e.g. Math, Statistics, Operations Research), Master's degree preferred - Strong SQL & Python 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. - Strong data analysis capabilities, with the ability to make data-driven fraud risk decisions.

About Rippling

Rippling gives businesses one place to run HR, IT, and Finance.

In the employer’s words · Read in context

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First seen by us
Oct 30, 2026 · today
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Job description

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About Rippling

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.


Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.


Based in San Francisco, CA, Rippling has raised $1.4B+ from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.


We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.

About the role

As a Fraud Strategy & Analytics Manager 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. You will be responsible for developing and enhancing fraud detection and risk mitigation strategies, with a focus on transaction fraud monitoring, fraud loss prevention, and fraud incident investigation, all while ensuring that decisions are based on robust analytics and large-scale data sets. Using data-driven insights, you will analyze transaction data, identify emerging fraud patterns, and collaborate with cross-functional teams including data science, security, compliance, product, and engineering to implement effective solutions. This is an excellent opportunity to leverage your expertise in data analytics and fraud prevention to drive strategic and impactful results, and grow your career in a fast-paced, dynamic environment. Your responsibilities will include:

What you will do

  • Develop and own fraud prevention strategies across Rippling’s financial products, including Payroll, Bill Pay, and Corporate Card, translating emerging fraud trends and business priorities into scalable risk mitigation solutions.
  • Design, implement, and optimize fraud monitoring and decisioning strategies using large-scale transaction data, behavioral signals, and risk indicators to improve fraud detection while minimizing false positives and friction for legitimate customers.
  • Drive fraud analytics and performance measurement by building dashboards, defining key risk indicators, and monitoring metrics such as fraud losses, detection rates, false-positive rates, and control effectiveness to guide strategy optimization.
  • Lead complex fraud investigations and root-cause analyses to uncover emerging fraud patterns, identify control gaps, assess financial exposure, and implement sustainable solutions to prevent recurring incidents.
  • Identify and proactively mitigate emerging fraud risks by analyzing transaction trends, monitoring evolving fraud typologies, and assessing vulnerabilities across products, customer segments, and payment flows.
  • Partner with Data Science and Engineering to develop and enhance fraud detection models, risk-scoring methodologies, analytical tools, and automated workflows that improve detection precision and operational scalability.
  • Collaborate cross-functionally with Product, Security, Compliance, Fraud Operations, and Customer Support teams to embed effective risk controls into product experiences, streamline investigation processes, and balance fraud prevention with customer experience and business growth.
  • Monitor and manage high-risk transactions and fraud incidents across financial products, making data-driven risk decisions, coordinating timely escalations, and driving resolution to minimize financial losses and customer impact.
  • Drive continuous improvement in fraud risk management by evaluating control performance, conducting post-incident reviews, and translating investigative insights into enhanced monitoring rules, risk policies, and prevention strategies.
  • Communicate fraud trends, analytical insights, and strategic recommendations to leadership and cross-functional stakeholders, influencing risk prioritization and driving measurable improvements in fraud prevention effectiveness.

What you will need

  • 5+ years experience in fraud prevention and detection, preferably in the financial technology sector, with a strong focus on payments, lending, and SaaS industries
  • Bachelor's degree in a relevant field (e.g. Math, Statistics, Operations Research), Master's degree preferred
  • Strong SQL & Python 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.
  • Strong data analysis capabilities, with the ability to make data-driven fraud risk decisions.
  • In-depth understanding of payments risks and funds flows, specifically within ACH and bank transfer fraud, account takeovers, wallet and corporate card transaction fraud.
  • Familiarity with the fraud investigation tools and industry-leading third-party risk vendors. Experience with fraud detection tools and methodologies is essential.
  • Effective communication and presentation skills, capable of articulating complex data and risk insights to various stakeholders.

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 accommodations@rippling.com


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.


#LI-Remote

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Pay

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Location & working pattern

New York, NY

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. #LI-Remote
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