Data Scientist Payment 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.comaddresses.

About the Role:

Rippling Payment Analytics team is looking for experienced and highly skilled Payments Platform Analytics Lead to join our fast growing team.

In this role, you will be responsible for designing, building, and maintaining services that automatically process massive amounts of financial data, providing visibility into each step of the money movement lifecycle in Rippling"s payments product ecosystem.

This is an exciting opportunity to become a foundational member of the Payments analytics team, where you'll be responsible for ensuring that our customers and external financial institutions correctly settle with Rippling on every single transaction.

It's a highly cross-functional role with significant visibility within the executive team. You will empower Accounting, Finance, Legal & Compliance, Payments, and product teams by delivering accurate data that not only are crucial to Rippling's financials but also play a significant role in guaranteeing the correct functioning of product systems at Rippling.

What you will do

• Collaborate across the company with engineering, accounting, financial partnerships and product teams to analyze and account for billions of dollars moving through the Rippling payment platform.
• Build full-cycle analysis using SQL, Python, or other scripting and statistical tools and develop real-time metrics dashboards to manage key financial and operating levers of the business.
• Monitor the payment flows between systems, banks, processors and inter-company, perform daily account reconciliations, and follow up on any discrepancies.
• React swiftly to issues which may arise, to summarize facts and provide recommendations for timely resolution of critical (real money) issues.
• Collaborating with key stakeholders (Accounting, Compliance, Treasury etc.) to understand business requirements and develop solutions to address reporting and reconciliation automation, including internal tool development and/or implementation of third party tools.
• Developing and maintaining documentation of reconciliation processes and procedures.
• Preparing and delivering data and reporting solutions supporting month-end close, regulatory & compliance reporting, Internal and External Audit reporting.
• Communicate findings and recommendations to stakeholders through clear and concise presentations and reports.
• Create, maintain and ensure completeness and accuracy of reporting databases, dashboards and collaborate with data engineering to implement, document, validate, and monitor our evolving data infrastructure.

What you will need

• Master's degree or Bachelor"s degree in Computer Science, Engineering, Statistics, MIS or other quantitative fields.
• 5+ years demonstrated experience in applying statistical analysis, modeling, machine learning and/or exploratory analysis to large datasets, ideally in payments processing, quote-to-cash financial reporting.
• Experience with data warehousing, ETL processes, and reporting tools (e.g., Snowflake, Tableau, DBT).
• Extensive experience with SQL, Python, or other scripting languages and their application to all phases of the data science development process (initial analysis and model development through deployment).
• Experience working with engineering, finance, and accounting teams to assess their data needs and build automated reporting pipelines.
• Strong problem-solving and communication skills, with the ability to communicate findings and recommendations clearly to both technical and non-technical audiences.
• Ability to interface with multiple stakeholders and senior leadership (C-suite) across the organization.
• Bonus point - Experience with general accounting principles, with the general ledger close process, and regulatory compliance.

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