Senior Data Architect

AI / ML Architect Banking & Credit Union Analytics

Experience:

Role Summary

define, design, and govern AI/ML solutions

Key Responsibilities

• Define

  AI/ML architecture and modeling strategy

  for banking analytics use cases.
• Design end-to-end solutions covering data ingestion, feature stores, model training, scoring, and monitoring.
• Guide teams in building

  predictive and prescriptive models

  aligned with business objectives.
• Ensure model explainability, fairness, and regulatory compliance.
• Work closely with business, risk, and technology leadership to shape analytics roadmaps.
• Review and approve model design, assumptions, and validation approaches.
• Establish standards for

  model governance, documentation, and lifecycle management

  .
• Mentor and work with ML engineers and ensure best practices are followed.

Required Skills & Experience

• 7–10 years of experience in AI/ML, with

  strong banking or credit union domain expertise

  .
• Proven experience architecting

  accounting

  ,

  collections, fraud, and risk analytics solutions

  .
• Deep understanding of banking data ecosystems and decision flows.
• Expertise in

  predictive, prescriptive, and decisioning models

  .
• Strong hands-on background in Python, ML frameworks, and SQL.
• Experience with cloud-based ML architecture and MLOps.
• Strong knowledge of regulatory, audit, and model risk management requirements.

Preferred

• Experience designing enterprise-scale ML platforms.
• Exposure to real-time fraud or decisioning systems.
• Leadership experience in guiding multi-disciplinary teams.