Job Description

The Model Risk Management Team is dedicated to ensuring regulatory compliance, supporting the reduction of potential errors or bias, and promoting appropriate utilization for models created and maintained by Block. The team achieves this by establishing and implementing robust model governance frameworks, validating and monitoring model performance, and providing guidance on best practices for model development and risk management.  This is a foundational team within compliance, which means it will support and collaborate with all key functional areas of Block regardless of the product or market.

We are looking for a Senior Quantitative Risk Analyst with model validation experience to join our team and support our model risk management activities. Your responsibilities will include validating machine learning models as applied to regulatory compliance such as anti-money laundering (AML), Know Your Customer (KYC), and sanctions screening. You will also provide analytical support and insights to improve our model development, and documentation standards.

In this role, you should have strong quantitative skills, attention to detail and knowledge of relevant regulations and industry best practices. You should also have excellent communication skills and the ability to work independently or as part of a team.

Responsibilities:

• Validate machine learning models using data analysis, testing procedures and quality assurance methods
• Evaluate and improve model validation activities, processes, and metrics
• Assess and advise on model governance frameworks, and development practices
• Identify and communicate model risks, issues, and gaps to management
• Provide analytical support and insights to improve model development, validation, and documentation standards
• Stay updated on emerging trends, developments and best practices in machine learning and compliance risk management
• Maintain validation documentation in accordance with internal policies and standards
• Develop continuous monitoring dashboards for ongoing model performance monitoring (e.g. model drift)
• Coordinate with cross-functional teams, particularly Data Science, Product, Engineering & Technology
• Develop effective stakeholder relationships and have a strong understanding of the businesses

Qualifications

Required: 

• Bachelors degree in the physics, economics, statistics, or a similar STEM field with 5+ years of related work experience; Graduate degree w/ 3+ years of relevant working experience; or 9+ years of relevant working experience
• Knowledge of data science modeling techniques, methodologies (e.g. familiarity with deep learning, boosted trees, and unsupervised learning)
• Experience with scripting and data analysis programming languages, such as Python (preferable) or R
• Advanced proficiency with SQL and data visualization tools (e.g. Tableau)
• Strong quantitative skills with the ability to interpret complex data sets
• Excellent communication skills with the ability to present technical information clearly and concisely 
• High ethical standards with a commitment to integrity and professionalism

Preferred:

• Experience in validating machine learning models related to compliance regulations such as AML, KYC, sanctions screening, or fraud detection 
• Prior experience in compliance risk management 
• Knowledge of regulatory frameworks such as SR 11-7