Risk Modeling, Data Governance Associate

Role Overview

• Serves as subject matter expert in designing and implementing data governance frameworks for key reporting and business processes
• Partners with business leaders to ensure data quality and timely delivery
• Performs independent challenge and validation of complex risk models
• Supports special projects as needed
• Identifies, documents, and assesses model data inputs to evaluate completeness, consistency, lineage, and effectiveness of controls
• Defines, documents, and executes data validation requirements for model validation activities
• Performs independent validation of statistical, machine learning, and Generative AI models
• Develops and executes benchmarks, challenger models, and replication analyses
• Assesses overall model health and compliance with data and model risk management policies
• Partners with model owners, developers, and business stakeholders to understand model design and business context

Requirements

• Bachelor’s Degree or equivalent work experience – Required
• Master’s Degree or higher in Statistics, Mathematics, Engineering, Computer Science, Economics, or a related field – Preferred
• 7+ years of experience working with statistical models, developing, and/or validating machine learning or Generative AI solutions, including rigorous testing and documentation – Required
• Quantitative or analytical professional background in Finance, Economics, Statistics, Mathematics, Engineering, or a related discipline – Required
• Experience in the financial services industry with exposure to data management, risk modeling, and regulatory compliance (e.g., BCBS 239, SR 11-7) – Required
• Prior consulting, advisory, or second-line oversight experience within data governance, model validation, or risk analytics environments – Preferred
• Knowledge of machine learning models, including development, validation, performance testing, and monitoring techniques
• Generative AI expertise, including evaluation of LLM architectures, design decisions, implementation approaches, and associated risks such as hallucinations, bias, and toxicity
• Hands-on experience with Retrieval-Augmented Generation (RAG) systems, including document ingestion, chunking strategies, embeddings, retrieval techniques, orchestration frameworks, and response grounding
• Hands-on experience with AWS-native services such as Bedrock, Lambda, API Gateway, S3, IAM, CloudWatch, and MLOps or LLMOps capabilities
• Strong Python proficiency for data manipulation, validation, automation of controls, and development of reproducible, well-documented scripts using version control
• SQL proficiency, including data extraction, joins, aggregation, reconciliation, and validation across multiple data sources
• Experience using Power BI to develop dashboards that visualize data quality metrics, trends, and validation outcomes.
• Proven ability to communicate complex technical, data, and model risk concepts clearly to non-technical governance and risk stakeholders.
• Strong analytical and critical thinking skills with the ability to independently challenge model assumptions and conclusions.
• Effective written and verbal communication skills, particularly in documenting and explaining complex technical and governance topics.
• Collaborative mindset with the ability to partner effectively with technical teams and business stakeholders.
• High attention to detail and a strong commitment to quality, accuracy, and governance standards.

Tech Stack

• AWS
• Python
• SQL

Benefits

• Competitive rewards package
• Health insurance
• Paid time off
• Flexible working arrangements
• Professional development opportunities