Model Risk Management Specialist
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What you'll do
- Reviewing model pre & post development documentation, data quality, accuracy, access and testing methodologies.
- Assessing model performance, accuracy, and stability.
- Evaluating model risk and identifying potential biases.
- Reviewing AI Models for AML/CFT Program
- Ensure that Transaction Monitoring and Customer Risk Assessment models comply with relevant AML/CFT regulations, including EU AML/CFT Directives, US BSA/AML regulations, and FATF recommendations.
- Conduct risk assessments to identify potential AML/CFT risks associated with Transaction Monitoring and Customer Risk Assessment models, including identifying higher-risk customer segments, products, and geographies, and assessing the effectiveness of controls and mitigants.
- Develop and implement procedures for ongoing model monitoring and maintenance, including annual reporting & certification, tracking model performance and identifying degradation, and conducting regular model reviews and updates.
- Collaborate with various stakeholders, including Model Engineering and owners, AML/CFT subject matter experts, and business units and risk management teams.
- Prepare and maintain high-quality documentation, including model validation reports, risk assessments, and regulatory compliance reports.
- Contribute to the development and maintenance of model validation methodologies, including developing and refining model validation frameworks, and identifying best practices and industry standards.
What they're looking for
- Bachelor's degree in a quantitative field (e.g., mathematics, statistics, computer science, engineering).
- 8+ years of experience in model validation, risk management, or a related field, preferably in AML/CFT.
- Strong understanding of machine learning and statistical modeling techniques.
- Deep understanding of fiat and crypto payment flows
- Proficiency in programming languages (e.g., Python, R, SQL).
- Experience with data visualization tools (e.g., Tableau, Power BI).
- Strong understanding of financial markets, products, and services.
- Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
Nice to have
- Professional certifications (e.g., FRM, CDA, CAP).
- Experience with AML/CFT transaction monitoring and Customer Risk Assessment systems
- Knowledge of cloud-based technologies.
- Experience with agile development methodologies.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Building the Future of Open Finance
Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system.
Before you apply, we encourage you to explore our culture page to understand what drives us and how we work.
The team
Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.
The opportunity
We are seeking a highly skilled and experienced Model Risk Management Specialist to join our team, focusing on Transaction Monitoring and Customer Risk Assessments models for Anti-Money Laundering (AML) and Combating the Financing of Terrorism (CFT) purposes. The successful candidate will be responsible for ensuring that our Transaction Monitoring, Customer Risk Assessment and Screening models are robust, effective, and compliant with regulatory requirements.
Model Validation: perform independent validation of Transaction Monitoring / Customer Risk Assessment / Screening models, AI models (built in Claude or ChatGPT), including but not limited to:
Reviewing model pre & post development documentation, data quality, accuracy, access and testing methodologies.
Assessing model performance, accuracy, and stability.
Evaluating model risk and identifying potential biases.
Reviewing AI Models for AML/CFT Program
AML/CFT Regulatory Compliance: ensure that Transaction Monitoring and Customer Risk Assessment models comply with relevant AML/CFT regulations, including but not limited to:
EU AML/CFT Directives.
US BSA/AML regulations.
FATF recommendations.
Risk Assessment: conduct risk assessments to identify potential AML/CFT risks associated with Transaction Monitoring and Customer Risk Assessment models, including but not limited to:
Identifying higher-risk customer segments, products, and geographies.
Assessing the effectiveness of controls and mitigants.
Model Monitoring and Maintenance: develop and implement procedures for ongoing model monitoring and maintenance, including but not limited to:
Annual reporting & certification
Tracking model performance and identifying degradation.
Conducting regular model reviews and updates.
Collaboration and Communication: collaborate with various stakeholders, including but not limited to:
Model Engineering and owners.
AML/CFT subject matter experts.
Business units and risk management teams.
Documentation and Reporting: prepare and maintain high-quality documentation, including but not limited to:
Model validation reports.
Risk assessments.
Regulatory compliance reports.
Methodology Development: contribute to the development and maintenance of model validation methodologies, including but not limited to:
Developing and refining model validation frameworks.
Identifying best practices and industry standards.
What you bring
Bachelor's degree in a quantitative field (e.g., mathematics, statistics, computer science, engineering).
5+ years of experience in model validation, risk management, or a related field, preferably in AML/CFT.
Understanding of international Model Risk Management rules and regulations, such as OCC SR 11-7.
Strong understanding of machine learning and statistical modeling techniques.
Deep understanding of fiat and crypto payment flows
Proficiency in programming languages (e.g., Python, R, SQL).
Experience with data visualization tools (e.g., Tableau, Power BI).
Strong understanding of financial markets, products, and services.
Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
Nice to haves
Professional certifications (e.g., FRM, CDA, CAP).
Experience with AML/CFT transaction monitoring and Customer Risk Assessment systems
Knowledge of cloud-based technologies.
Experience with agile development methodologies.
Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.
Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.
We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Our commitment
Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto.
We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision.
As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.
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