Model Risk Specialist

Responsibilities

• Conduct independent reviews of data and infrastructure environments used for AI/ML models
• Evaluate risks across the model lifecycle including feature engineering, CI/CD, and deployment platforms
• Assess data governance practices such as quality, lineage, and access controls
• Establish and enhance controls and validation practices for model development infrastructure
• Partner with platform teams to define and monitor Key Risk Indicators (KRIs)
• Develop tools, analyses, and playbooks for infrastructure and data risk management
• Build reporting and monitoring solutions for model infrastructure health
• Collaborate with model teams and data engineers to drive risk-aware design decisions

Requirements

• Bachelor's or master's degree in Computer Science, Data Science, Statistics, Mathematics, or Engineering
• Proficiency in Python and SQL
• Hands-on familiarity with MLOps, CI/CD pipelines, feature stores, and cloud ML platforms (AWS, GCP, or Azure)
• Understanding of Data Mesh architecture, data lineage, and data quality frameworks
• Experience with model monitoring concepts like drift detection and pipeline stability
• Strong written and verbal communication skills in English
• Understanding of risk management principles and governance frameworks

Preferred Qualifications

• Experience in a 2nd or 3rd line of defense
• Prior experience in model risk management, model validation, or ML engineering
• Familiarity with regulatory frameworks such as SR 11-7 or NIST AI RMF
• Experience with Spark or Scala

Benefits

• Equity opportunities
• Meal and food cards
• Commuting benefits
• Psychological, financial, and legal assistance
• Medical, dental, and life insurance
• Language course program and learning platform
• Extended parental leave and daycare allowance
• Work-from-home allowance
• Gym partnerships
• 30 days of paid vacation
• Relocation assistance package