Internal Audit Model Risk Manager

Coinbase Careers Page

5h • Hybrid

About The Position

Ready to be pushed beyond what you think you’re capable of?
At Coinbase, our mission is to increase economic freedom in the world. It’s a massive, ambitious opportunity that demands the best of us, every day, as we build the emerging onchain platform — and with it, the future global financial system.
To achieve our mission, we’re seeking a very specific candidate. We want someone who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system. We want someone who is eager to leave their mark on the world, who relishes the pressure and privilege of working with high caliber colleagues, and who actively seeks feedback to keep leveling up. We want someone who will run towards, not away from, solving the company’s hardest problems.
Our work culture is intense and isn’t for everyone. But if you want to build the future alongside others who excel in their disciplines and expect the same from you, there’s no better place to be.
While many roles at Coinbase are remote-first, we are not remote-only. In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.
The Coinbase Internal Audit is an independent, third line function that reports directly to the Coinbase Audit Committee. The purpose and mission of Internal Audit is to objectively evaluate and audit the effectiveness of governance, compliance, risk management, and control process. The in-house Coinbase Internal Audit team is responsible for strategic analysis, risk assessments, development of the audit plan, project management, quality review, report issuance and issue validation across IT and business functions. By executing all aspects of audits, including planning, walkthroughs, testing, deficiency remediation, and report writing in accordance with the Irish regulatory requirements, you'll play a key role in strengthening our position as the industry leader by evaluating the effectiveness of management’s ability to control potential events or threats and ultimately add value to all our stakeholders.

Requirements

• A BA/BS degree in Statistics, Mathematics, Economics, Data Science, Engineering, or related quantitative fields.
• 8+ years of experience, with at least 5 years of experience in Model Risk Management, Model Validation, or Quantitative Audit within the financial services or fintech industry.
• Specific experience with Financial Crime models: Deep understanding of the logic, data inputs, and tuning methodologies for AML Transaction Monitoring (rules-based and machine learning), Sanctions Screening (fuzzy logic, NLP), and Fraud models.
• Technical Proficiency: Ability to read and review code. Proficiency in statistical programming languages such as Python, R, SQL, or SAS is essential.
• Excellent understanding of the model development lifecycle (MDLC) and internal control environments surrounding data governance and model implementation.
• Proven project management skills with the ability to juggle multiple complex technical validations and deadlines.
• Solid analytical and problem-solving skills, with high standards for quality, accuracy, and attention to detail.
• Excellent written and verbal communication skills; ability to explain models to non-technical stakeholders.
• Experience leading and managing technical or co-sourced teams.
• Experience auditing machine learning/AI models and/or familiarity with AI governance frameworks.

Nice To Haves

• Advanced Degree (Masters or PhD) in a quantitative discipline.
• Experience working in a fast-paced organization or high-growth tech company.
• Entrepreneurial attitude and experience with, or the ability to adapt to, a rapidly growing start-up with associated complexities and ambiguities.
• Understanding of crypto, blockchain analytics (e.g., Chainalysis, TRM Labs), and the specific challenges of modeling risk on the blockchain.
• Professional certifications such as FRM (Financial Risk Manager), PRM, or CAMS-FCI (Financial Crimes Investigations).
• Experience auditing machine learning/AI models and/or familiarity with AI governance frameworks.

Responsibilities

• As a part of a global internal audit team, lead the development of next-generation model audit practices to maintain a best-in-class global internal audit function, specifically focusing on the integrity of algorithms driving the business.
• Responsible for supporting the internal audit plan through the execution of technical model validations and model risk audits from beginning to end. Key activities include independent replication, code review, conceptual soundness assessment, back-testing analysis, and validation of remediated model findings.
• Lead the validation of critical Financial Crime Compliance models, including Transaction Monitoring, Sanctions Screening, Customer Risk Rating, and Fraud detection models. You will ensure these models operate effectively and align with global regulatory requirements.
• Review and evaluate the adequacy of management's response to audit findings, including the validation of complex remediation activities involving data lineage and algorithm tuning.
• Develop technical audit reports on the effectiveness of model performance and governance for an executive-level audience, translating complex quantitative concepts into clear, actionable business insights.
• Assist in the preparation of internal audit materials regarding the Model Risk portfolio for the Audit Committee and Board of Directors.
• Establish and maintain trusted relationships with Data Science, Engineering, Product, and Compliance teams to foster a culture of robust model governance.
• Work closely with first and second lines of defense to maximize testing efficiencies and ensure comprehensive coverage of the model inventory, minimizing duplication of efforts while maintaining 3rd Line independence.
• Serve as a value-add advisor to business partners by identifying opportunities to enhance model precision, reduce false positives, and improve operational performance without compromising objectivity.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees