Overview In this role you will design and deliver AI-powered analytics for Internal Audit, from scoping to reporting. You will collaborate with audit teams across the lifecycle to build SQL, Python, and Tableau solutions that strengthen defensibility and insight. You'll apply AI tooling to accelerate analysis, craft audit work products, and support governance tooling. This position sits at the intersection of data, risk, and technology, enabling robust, transparent audits at scale.
Compensation / Benefits- time off programs
- medical, dental, vision
- mental health support
- paid parental leave
- life and disability insurance
- 401(k) and employee stock purchase program
Responsibilities- Partner with Internal Audit teams across the audit lifecycle to deliver suitable AI and analytics capabilities
- Develop optimized SQL queries and AI prompts to extract and reconcile high-volume data from financial, operational, and source platforms
- Create Python scripts for data cleaning, transformation, and repeatable audit testing
- Leverage AI tools to speed data analysis, summarize findings, draft work papers, and build lightweight internal tooling
- Design audit-ready visualizations and Tableau dashboards communicating risk and findings to technical and non-technical stakeholders
- Develop understanding of in-scope business systems to assess data lineage, controls, and risk
- Provide light system administration support for GRC and other tooling (user access, workflow configuration, troubleshooting)
- Identify AI/analytics opportunities and data quality issues, flag risk trends, and pursue automation opportunities
- Support training for audit staff on analytics tools and AI-assisted workflows
- Document methodology, assumptions, and results for re-run, review, and defense by leadership and external reviewers
Key requirements- 2-4 years of experience in AI, agentic AI, data analytics, audit analytics, BI, or related analytical role
- 1-2 years of experience in audit, internal audit, risk security or related field
- Experience building production-grade LLM systems, agents, tool integration, retrieval/grounding, and prompt optimization
- Strong agent engineering principles and safe failure handling
- Strong proficiency in SQL for large, complex datasets
- Working proficiency in Python for data analysis and scripting
- Capability to use probabilistic models and tune for deterministic, audit-defensible results
- Experience building dashboards or reports in Tableau or a comparable BI tool
- Ability to quickly learn business systems and gather stakeholder requirements
- Proactive, self-starting, problem-solving mindset
- Comfort with basic system administration on platforms like an eGRC tool
- Strong written and verbal communication skills including training non-technical colleagues
- Bachelor's degree in a quantitative, business, accounting, or related field, or equivalent practical experience
- proactive, self-starting
- strong written and verbal communication
- ability to train non-technical colleagues
- SQL
- Python
- Tableau or comparable BI tool
