Audit - Valuation & Analytics - AI Specialist
- Support engagement teams in identifying and documenting how client entities are using AI - across financial reporting processes and broader enterprise functions - including intelligent automation, AI agents, and agentic systems.
- Assist in evaluating AI model complexity, reliability, and performance - applying statistical and quantitative methods to assess model inputs, outputs, and assumptions, including drift and year-over-year change, under the direction of senior team members.
- Help assess governance structures and risk management practices around AI systems, referencing recognized frameworks (e.g., NIST AI RMF, ISO/IEC 42001) as part of broader team assessments.
- Support the preparation of assessment reports, maturity scorecards, and other client deliverables that document governance gaps and recommended remediation.
- Support the evaluation of process vs. control determinations, including the appropriateness of human oversight and monitoring controls over AI systems (e.g., human-in-the-loop reviews, KPI monitoring controls).
- Assist in designing audit responses to AI-related risks, including controls testing over AI governance, data inputs, and model outputs.
- Support planning and execution of substantive procedures over account balances and transactions impacted by the use of AI (e.g., accounting estimates derived from ML models, automated journal entries, AI-driven reconciliations).
- Support day-to-day communication with client working teams (e.g., IT, risk, business process owners) as part of the broader engagement team.
- Assist in preparing materials and supporting analysis for status updates and workshops with client stakeholders.
- Communicate technical AI/ML concepts clearly in team settings and client working sessions, under the guidance of senior team members.
- Stay current on developments across the AI landscape and contribute to internal training materials and team knowledge-sharing.
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to provide clear guidance to others
Required:
- Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, Accounting, Finance, or a related field.
- 1+ years of experience in AI/ML, risk and controls, external or internal audit, advisory, or a technology-focused role (internship experience welcome).
- Foundational knowledge of machine learning, generative AI, LLMs, and agentic/RAG-based systems - how they're built, validated, monitored, and where they can fail.
- Basic understanding of internal controls frameworks (e.g., COSO, ICFR) and risk assessment principles.
- Exposure to model evaluation concepts, such as assessing model accuracy, robustness, and fitness for purpose.
- Solid grounding in statistics and quantitative methods - including regression, hypothesis testing, and probability.
- You should reside within a commutable distance of your assigned office with the ability to commute daily, if required.
- You should expect to co-locate with team members or other colleagues in a Deloitte office, at a client site and/or virtually, based on specific team and business expectations.
- Ability to travel up to 25%, on average, based on the type of work you perform and the clients served.
- Limited immigration sponsorship may be available.
- Hands-on experience with AI/ML tools - e.g., Python (scikit-learn, pandas, PyTorch/TensorFlow), cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI), or similar.
- Familiarity with the AI regulatory landscape - including the EU AI Act, NIST AI RMF, and related standards.
- Exposure to advisory or assurance engagements involving organizational governance, risk, or controls (e.g., IT general controls reviews, enterprise risk assessments) outside of the financial statement audit.
- Master's degree in Computer Science, Data Science, Information Systems, Statistics, or a related field.
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