Join Rippling's Payments Data & Analytics team as an experienced Data Scientist. This role is central to our customer funds analytics, focusing on data reconciliation, quality enhancement, and ensuring the scalability and robustness of our payments reconciliation platform.

You will collaborate closely with Engineering, Product, and Finance teams to provide customers with clean, actionable data. The position requires strong critical thinking to dissect complex issues and a proactive approach to working cross-functionally in a fast-paced setting, covering the entire data stack from engineering to strategic recommendations.

This is a foundational opportunity for someone eager to build analytics capabilities from the ground up.

Develop internal tools and processes for reconciling financial and transactional data across various sources to facilitate accurate, repeatable customer funds reporting.

Partner with Accounting, Compliance, and Engineering to understand business needs and create automated solutions for reporting and reconciliation, including the development or implementation of third-party tools.

Uphold robust internal controls to prevent payment errors and ensure compliance.

Provide support for audits, month-end reconciliations, system implementations, and special projects.

Utilize data analysis and AI-driven tools to identify process inefficiencies, detect anomalies, and drive automation opportunities. Enhance the performance and reliability of DBT pipelines and contribute to evolving the broader data architecture.

A minimum of 4 years of experience in Business Intelligence or Data Analytics, ideally within Finance, Accounting, or Compliance.

Excellent communication and presentation skills, with the ability to articulate problems and findings to all organizational levels.

Demonstrated success in cross-functional collaboration and presenting insights to executive leadership.

Experience partnering with Finance and Accounting teams on detailed, data-intensive reconciliations involving disparate datasets.

Proficiency in reconciling financial or transactional data, preferably in e-commerce or payments.

Familiarity with data warehousing and reporting technologies such as DBT, Snowflake, or Tableau.

Expert-level SQL skills are essential.

Understanding of business intelligence best practices and tooling.

Knowledge of data transformation best practices and tools (e.g., dbt projects, incremental tables).

Experience with data visualization tools and delivering self-service reporting capabilities.