Director of Mortgage Operations Analytics AI

📋 Description

• • Own the end-to-end analytics and AI roadmap for AmeriSave’s mortgage operations, translating complex data into clear, actionable insights that materially reduce cycle times, cut costs, and elevate borrower experience.
• • Architect and maintain a scalable data ecosystem that ingests loan-level data from origination, processing, underwriting, closing, and post-closing systems; ensure data integrity, lineage, and governance across Snowflake, SQL Server, and cloud-native warehouses.
• • Design, validate, and deploy predictive models (e.g., default risk, pull-through probability, capacity forecasting) using Python, R, SAS, or Spark; champion MLOps best practices so models move from notebook to production with automated testing, monitoring, and retraining.
• • Build executive-grade dashboards in Tableau, Power BI, or Looker that surface real-time KPIs—turn time, fallout rates, underwriting exceptions, funding velocity—enabling VPs and department heads to spot bottlenecks within minutes, not days.
• • Partner daily with Processing, Underwriting, Closing, Post-Closing, Capital Markets, and Compliance leaders to translate business pain points into analytic hypotheses; run A/B tests and quasi-experiments that prove ROI before scaling solutions enterprise-wide.
• • Lead a high-performing team of 6–10 data scientists, analysts, and data engineers; set clear OKRs, mentor on advanced techniques (gradient boosting, NLP on loan files, computer vision on documents), and cultivate a culture of experimentation and continuous learning.
• • Drive AI innovation: pilot large-language-model applications for automated stipulation gathering, deploy computer vision to classify and extract data from 1,000-page loan packages, and leverage reinforcement learning to optimize loan officer scheduling.
• • Establish and enforce data governance policies that satisfy SOX, CFPB, and state regulatory requirements; partner with Legal and Compliance to ensure model explainability and fairness testing for all consumer-facing algorithms.
• • Present findings to the C-suite and Board Risk Committee on a monthly cadence, translating technical results into strategic narratives that influence multi-million-dollar investment decisions and capital market pricing strategies.
• • Benchmark AmeriSave’s operational metrics against industry peers using MISMO, HMDA, and proprietary lender consortium data; identify gaps and spearhead initiatives that move the organization into the top quartile for speed, quality, and cost.
• • Create self-service analytics capabilities for 500+ operations staff—parameterized reports, natural-language query bots, and alert systems—reducing ad-hoc requests on your team by 40% while democratizing data access.
• • Oversee vendor selection and contract negotiation for third-party AI tools (OCR, chatbots, predictive dialers); ensure seamless integration with existing tech stack and rigorous ROI measurement post-implementation.
• • Champion change management: develop playbooks, training curricula, and incentive structures that embed data-driven decision-making into daily workflows, turning skeptical underwriters into enthusiastic power users.
• • Continuously scan the horizon for emerging technologies—graph neural networks for fraud detection, synthetic data generation for model training, quantum-inspired optimization for hedging pipelines—and craft 3-year technology roadmaps that keep AmeriSave ahead of the curve.