Rippling is looking to solve the problem of fraud risk across its financial products, including Payroll, Bill Pay, and Card Transactions, by developing robust data-driven risk strategies to enhance fraud detection and prevention capabilities.
Requirements
- 1+ year of experience in data science and analytics: Demonstrated experience in using analytics and data science techniques to solve fraud-related challenges, particularly in financial technology, payments, or SaaS industries.
- Expertise in data analysis: Proficient in extracting insights from large datasets, with hands-on experience using tools such as Python, R, SQL, and other data analysis platforms to create robust fraud detection strategies.
- Data-driven approach to decision-making: Experience in developing data-driven strategies that address fraud risks while balancing the impact on customer experience and operational efficiency.
- Effective cross-functional collaboration: Proven ability to collaborate with product, risk, security, and engineering teams to drive fraud risk initiatives.
- Experience with machine learning models: Familiarity with building and deploying machine learning models for fraud detection.
- 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.
- Educational background: Bachelor's degree in a relevant field such as Data Science, Mathematics, Statistics, or Operations Research. A Master’s degree is preferred.
Responsibilities
- Develop data-driven fraud detection strategies: Use advanced analytics to design and enhance fraud detection strategies that address risk in real-time across multiple financial products, including transaction monitoring, onboarding, and account takeover (ATO) detection.
- Analyze fraud patterns and risk trends: Perform deep analysis on transactional data to identify fraud patterns, emerging threats, and vulnerabilities, and translate these findings into actionable risk mitigation strategies.
- Collaborate across teams: Work closely with Fraud Risk Strategy, Security, Product, and Engineering teams to align fraud prevention initiatives with business goals, ensuring analytics-driven decisions are integrated into product development and operational workflows.
- Conduct comprehensive cost-benefit analyses: Evaluate the trade-offs between fraud risk reduction, customer experience, and operational efficiency to develop optimal fraud prevention strategies.
- Enhance ATO detection through data analysis: Use data analytics to identify suspicious behaviors and enhance ATO detection, working closely with the security team to define rules, analyze data, and measure effectiveness.
- Monitor and refine risk strategies: Continuously assess and improve fraud detection strategies based on new data insights, fraud trends, and ongoing performance evaluations to stay ahead of emerging fraud tactics.
- Partner with R&D to design, build, and maintain tools for fraud detection and investigation, ensuring they meet evolving business needs.
Other
- Bachelor's degree in a relevant field such as Data Science, Mathematics, Statistics, or Operations Research. A Master’s degree is preferred.
- 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.
- 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 accomodations@rippling.com
- A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location.
