About the role
Manager - Financial Risk Analytics Manager - Financial Risk Analytics 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 the Manager for the Financial Risk Analytics at Rippling, you will lead the advanced financial risk analytics and forecasting functions to manage and mitigate financial and operational risks across Rippling’s financial product suite. You will be responsible for setting the strategy for risk forecasting, loss provisioning, and data-driven reporting. This is a critical leadership role for an individual with a proven track record of managing technical teams and translating complex analytics into strategic business recommendations for senior leadership. What you will do Lead Advanced Analytics and Forecasting : Direct a team focused on advanced analytics and forecasting methodologies, ensuring the development of cutting-edge risk management capabilities. Risk Loss Provisioning : Lead the modeling and forecasting of risk loss provisioning, working closely with Finance and Accounting teams to ensure accuracy and compliance. Forecasting Risk Servicing Volumes : Develop models and forecasts for risk servicing volumes to inform capacity planning and resource allocation. Risk MIS and Multi-Taxonomy Reporting : Put together a comprehensive risk portfolio reporting for a complex set of products and work across multiple taxonomies to report on various risks to the organization (e.g., financial, operational risk) to senior management. Automated Analytics Dashboards : Design, implement, and maintain automated analytics dashboards and reporting mechanisms to provide senior stakeholders with clear, timely, and actionable insights into credit risk performance and emerging trends. Strategic Collaboration : Partner with Product, Engineering, Risk Strategy, and Finance teams to integrate risk insights into product development, operational workflows, and overall corporate strategy. Team Leadership and Development : Mentor and manage a team of risk data scientists and analysts, fostering a culture of rigorous analysis, innovation, and high-quality execution. What you will need 5-8 years of experience in data science and risk analytics : Proven ability to use advanced analytics and data science methods to address complex risk-related challenges, specifically within the financial or fintech industries. 3+ years of experience in leading teams : Demonstrated success in leading and managing advanced analytics or forecasting teams and functions. Deep Experience in Risk Loss Provisioning : Hands-on experience with modeling, forecasting, and reporting for risk loss provisioning (e.g., CECL, IFRS 9). Educational background : Master’s degree or PhD in a quantitative field such as Data Science, Mathematics, Statistics, Economics, or a related discipline. Expert Proficiency in Data Analysis & Modeling : Expert-level hands-on experience with Python, R, SQL, and robust familiarity with version control (e.g., Git). Executive Communication and Stakeholder Management : Exceptional communication skills with the ability to clearly articulate complex technical findings, strategic risks, and opportunities to both technical and non-technical senior stakeholders.
