Model Risk Management Specialist

Kraken; Brasil; Presencial; BRL 180 000 - 300 000; Tempo integral

Resumo da oferta

Kraken is actively seeking a highly skilled Model Risk Management Specialist to join our team, focusing on Transaction Monitoring and Customer Risk Assessments models for AML/CFT purposes. The role ensures robustness, effectiveness, and regulatory compliance of our models.

The ideal candidate will bring 5+ years in model validation or risk management, strong ML knowledge, programming skills in Python/R/SQL, and experience with financial markets and crypto payment flows.

Qualificações

• 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.

Responsabilidades

• Model Validation: perform independent validation of Transaction Monitoring / Customer Risk Assessment / Screening models, AI models, including review of docs, data quality, accuracy and testing methods.
• AML/CFT Regulatory Compliance: ensure models comply with AML/CFT regulations (EU, US, FATF).
• Risk Assessment: identify AML/CFT risks across customer segments, products, and geographies.
• Model Monitoring and Maintenance: develop procedures for ongoing monitoring, annual reporting, and updates.
• Collaboration and Communication: work with model engineers, SMEs, risk teams, and business units.
• Documentation and Reporting: produce validation reports, risk assessments, and regulatory reports.
• Methodology Development: contribute to model validation frameworks and best practices.

Conhecimentos

Python

R

SQL

ML techniques

Data visualization

Communication

Financial markets

AML/CFT knowledge

Formação académica

Bachelor's degree in a quantitative field

Ferramentas

Tableau

Power BI

Descrição da oferta de emprego

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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