> Markdown version of [/jobs/ext/3885033-senior-data-analytics-internal-auditor](https://www.wearedevelopers.com/jobs/ext/3885033-senior-data-analytics-internal-auditor). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Analytics - Internal Auditor - **Company:** Robert Half - **Location:** Chicago, IL, United States (Remote available) - **Experience:** Expert - **Salary:** $100,000.0 - $121,000.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Computer Programming, Data Validation, Data Systems, R (Programming Language), JD Edwards EnterpriseOne, Python (Programming Language), Data Driven Tests, Salesforce.Com, SQL Databases, Scripting, Enterprise Software Applications, Information Technology, Data Analytics, Workday - **Published:** October 23, 2026 - **Apply:** https://www.chicagocareersite.com/job.asp?id=3466730316&tx=JT989TYI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 5+ years of progressively responsible experience applying advanced data analytics, automation, and data-driven control testing within Internal Audit, SOX, compliance, and/or enterprise risk environments. * Bachelor's degree or equivalent in Computer Science, Data Science, Management Information Systems, Accounting, Finance, or a related field. * Proven track record of delivering audit and risk solutions through the application of data analytics, scripting, and programming skills (e.g., Python, R, SQL) and relevant analytics platforms. * Strong experience across the full data analytics lifecycle, including data acquisition, cleansing, transformation, analysis, and reporting. * Experience designing and delivering continuous auditing capabilities, dashboards, and monitoring solutions that provide reliable, timely performance metrics and actionable insights. * Experience working with enterprise platforms such as Workday, JD Edwards (JDE), Salesforce, and similar systems, including extracting, analyzing, and validating data for audit and risk purposes. ## Description * Lead the Internal Audit data analytics function, serving as the primary point of expertise for data analytics, automation, AI-enabled solutions, and continuous auditing within the department. * Apply a data-driven mindset to build, enhance, and execute Internal Audit data solutions that deliver advanced audit capabilities, including automation, continuous auditing, and data analytics. * Lead and oversee data analytics initiatives supporting audit, SOX, and risk projects, leveraging advanced analytical techniques to enhance audit procedures, expand coverage, and identify risks. * Design and execute data-driven testing of key controls across in-scope processes, systems, and programs, elevating levels of assurance, consistency, and audit efficiency. * Develop and implement AI-enabled and advanced analytics solutions using available tools to support audit teams and audit operations. * Drive automation across audit, SOX, and risk activities, unlocking efficiencies and improving the quality and scalability of testing and analysis. * Develop and enhance continuous auditing capabilities, including dashboards and monitoring solutions that provide timely control and business insights to support management action. * Serve as a data champion within Internal Audit by elevating awareness of appropriate, effective, and responsible uses of data in assurance and advisory work. * Collaborate closely with audit teams to integrate analytics into audit planning, execution, and reporting activities. * Build and maintain strong relationships with key data leaders, system owners, and data custodians to enable timely and reliable access to data required for audit and risk initiatives. * Leverage enterprise systems such as Workday, JD Edwards (JDE), Salesforce, and other core platforms as key data sources to support audit analytics, continuous auditing, and data-driven control testing. * Use existing data sources and structures to provide more quantitative, evidence-based assessments of key risks, controls, and audit conclusions.