Head of Internal Audit - Head of Innovation Strategy

Internal Audit

In Internal Audit, we ensure that Goldman Sachs maintains effective controls by assessing the reliability of financial reports, monitoring the firm’s compliance with laws and regulations, and advising management on developing smart control solutions. Our group has unique insight on the financial industry and its products and operations. We’re looking for detail-oriented team players who have an interest in financial markets and want to gain insight into the firm’s operations and control processes.

Position Overview

The Head of Internal Audit Innovation Strategy will lead the design, delivery, and institutionalization of cutting-edge technology, artificial intelligence (AI), advanced analytics, and automated testing across the global Internal Audit department.

Reporting to senior audit executive leadership, this individual will sit at the intersection of internal audit, data science, engineering, and digital transformation. The VP will lead a team of analytics and innovation specialists to re-imagine traditional audit approaches, drive continuous risk assessment, scale automated assurance solutions, and prepare the department for AI-enabled operational models.

Key Responsibilities

1. Innovation Strategy & AI Roadmap Execution

• AI & Automation Vision: Define and execute a multi-year digital strategy for Internal Audit, focusing on Generative AI, Agentic AI, Large Language Models (LLMs), machine learning, and Process Automation (RPA) to automate repetitive audit tasks and scale risk detection.
• Use-Case Pipeline Management: Identify, prioritize, and manage high-ROI audit innovation use cases across the full audit lifecycle (planning, risk assessment, field testing, continuous monitoring, and reporting).
• Auditing Emerging Tech & AI Governance: Establish robust methodologies and control frameworks to audit organizational AI systems, algorithms, and data governance frameworks for bias, drift, and regulatory compliance.

2. Analytics Platform & Continuous Monitoring Delivery

• Scalable Data Solutions: Oversee the development and maintenance of scalable data analytics products, interactive dashboards, and automated continuous risk monitoring tools (leveraging SQL, Python, Alteryx, Tableau/PowerBI, and enterprise data platforms).
• Audit Integration: Partner directly with business, technology, and capital markets audit execution teams to embed risk analytics and continuous auditing techniques into standard audit plans.
• Data Engineering & Infrastructure: Direct delivery teams (data scientists, data engineers, automation architects, and business analysts) in maintaining data pipelines, integrating disparate legacy architectures, and ensuring data quality across audit tools.

3. Capability Building, Upskilling & Change Management

• Digital Literacy & Adoption: Design and deploy comprehensive enablement programs (e.g., custom AI assistant adoption, Copilot training, low-code/no-code analytics workshops) to upskill non-technical auditors and achieve high adoption rates across the department.
• Culture of Innovation: Champion a forward-thinking audit culture that embraces curiosity, automation, and agile delivery principles.

4. Leadership, Stakeholder & Regulatory Governance

• Senior Stakeholder Management: Communicate technical concepts, innovation roadmaps, and business impact clearly to the Audit Committee, Executive Management, business line leaders, and external regulators.
• Team Leadership & Development: Recruit, mentor, and manage a high-performing team of data analytics and technology innovation specialists across global hubs.

Qualifications

• Experience: 8–12+ years of progressive leadership experience in Internal Audit, Technology Audit, Risk Analytics, or Technology Consulting, ideally within Financial Services or Investment Banking.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Finance, Accounting, or a related quantitative field.
• Certifications: CISA, CIA, ACCA/CPA, or relevant data/AI technical certifications strongly preferred.
• Technical Proficiency:
  • AI & ML: Hands-on experience or strategic oversight of Generative AI, LLM prompting/fine-tuning, Agentic workflows, and machine learning/predictive modeling.
  • Data Analytics & Tools: Mastery in SQL, Python/R, data visualization platforms (Tableau/Power BI), and data preparation tools (e.g., Alteryx, Snowflake).
  • Audit Methodology: Deep understanding of internal audit methodologies, COSO, risk assessment, and regulatory expectations in financial services.
• Leadership & Influence: Proven track record of leading matrixed digital transformation projects, managing data teams, and presenting to senior executive committees.

About Goldman Sachs

 At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.   

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2026. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.