Senior Data Analyst, Internal Audit

Navan•New York City, NY

About The Position

We are looking for a driven Internal Audit Data Analyst to join our team. This is not a traditional auditing role; it is a build role. You will report to the Senior Manager of Internal Audit and help transform our department from a retrospective testing function into a proactive, data-driven risk monitor. In this role, you will leverage Snowflake to mine transactional datasets (travel bookings, card swipes, and SaaS subscriptions) and build self-service "Liveboards" in ThoughtSpot that allow our auditors and business stakeholders to monitor risk in real-time. You will be expected to champion a data-first mindset, challenging the status quo to enhance the effectiveness, efficiency, and scalability of our internal control environment.

Requirements

Bachelor’s degree in Data Science, Computer Science, Information Systems, or a quantitative field (Business/Finance degrees acceptable with strong technical portfolio).
5+ years of relevant experience in data analysis, specifically within an Audit, Risk, Compliance, Finance, or Forensic context.
Technical Expertise: Querying: Advanced proficiency in SQL is required. You must be comfortable writing complex queries (joins, window functions, CTEs) against Snowflake.
Visualization: Experience connecting cloud data to ThoughtSpot. You understand Worksheets, Views, and Search capabilities. You know how to model data specifically so that ThoughtSpot’s search engine returns accurate results.
Data Quality (C&A): A rigorous approach to validating "Completeness and Accuracy." You don't just visualize data; you first prove it matches the source system (NetSuite/Product Backend).
Analytical Curiosity: A strong sense of curiosity and the ability to ask probing questions to understand complex business processes and data context.
Builder Mindset: A self-starter who proactively identifies problems and builds tools to fix them, while maintaining the flexibility to jump in and support team priorities when needed.
Communication: The ability to translate complex data findings into clear, actionable audit conclusions for non-technical stakeholders.

Responsibilities

Analytics Engineering & Automation Design and develop SQL queries and Python scripts to support operational audit activities. This includes building automated audit tests, anomaly detection models, and risk scoring mechanisms to replace manual sampling.
Develop techniques for continuous auditing, moving us away from point-in-time testing. You will build and maintain models that analyze large volumes of data for outliers, patterns, and trends.
Partner with the SOX team to automate ITGC and Business Process control testing. Your goal is to achieve 100% population testing on key controls rather than relying on random sampling.
Visualization & Risk Intelligence Create dynamic visualizations that provide management with real-time insights into Key Risk Indicators (KRIs) and emerging risk trends.
Design and execute data analytics for Enterprise Risk Management (ERM) initiatives, providing data-driven support for annual risk assessments.
Model data in ThoughtSpot to empower non-technical auditors to ask their own questions (e.g., "Show me duplicate expense submissions > $500 last month").
Strategic Partnership Interact with Engineering, Data Science, and Business Operations to identify appropriate data sources.
You will validate the completeness and accuracy (C&A) of data received to ensure it meets audit standards.
Champion a data-first mindset within the team. You will research and communicate best practices, teaching traditional auditors how to utilize data tools to improve their process.
Collaborate closely with the core audit team, occasionally assisting with broader departmental initiatives or fieldwork support to ensure team deadlines are met.