VP, Mortgage Data Analytics

Equifax, Inc. in; St. Louis (MO); On-site; USD 200,000 - 300,000; Full time

Job summary

Equifax Inc. seeks a VP of Mortgage Data Analytics to lead end-to-end analytics for one of WS’s largest businesses.

You will partner with Mortgage leadership on strategy, pricing and product insights, driving revenue growth and lender value through advanced data products and AI-enabled analytics. You will shape the analytics roadmap, collaborate with cross-functional leaders, and shepherd data-driven decision making across origination, servicing and portfolio retention in a high-impact mortgage

Qualifications

• Bachelor’s degree required with 10+ years in analytics leadership and data teams.
• Proven revenue, penetration or retention outcome from embedding analytics in a business line.
• Strong technical foundation in SQL and Python; experience with modern BI tools and cloud data platforms.

Responsibilities

• Define and run analytics roadmap aligned to Mortgage WS revenue, product and retention goals.
• Serve as trusted partner to Mortgage leadership and cross-functional teams.
• Lead AI-native operating model and scale analytics with AI/LLM tools to automate reporting and insights.
• Package data assets into reusable products and pilot ROI studies to prove value.

Skills

Analytics leadership

SQL

Python

AI/ML

Stakeholder mgmt

Education

Bachelor's degree

Tools

BigQuery

BI tools

Job description

As VP, Mortgage Data Analytics, you will be the analytics leader with full end-to-end accountability for one of Equifax Workforce Solutions (WS) largest and most strategic businesses. Income and employment verification through The Work Number is part of millions of U.S. mortgage decisions. Your job is to turn that data into insight, products and growth for our lenders and for the WS Mortgage business.

You will be a trusted partner to the Mortgage SVP/GM and leadership team, in the room when pricing, product, sales and market strategy decisions are made. You will understand the full mortgage lifecycle (pre-qualification, origination, underwriting, pre-close re-verification, servicing and portfolio retention) and how rate cycles, refi and purchase mix, GSE policy and lender economics shape demand for verification.

This position does not offer immigration sponsorship (current or future) including H4, H1B transfer or F-1 STEM OPT extension support.

What you’ll do

Three Core Pillars of Responsibility

1. Embedded Strategic Partner to the Mortgage Business

• Analytics strategy owner: Define and run the analytics roadmap for WS Mortgage, tied directly to the business's revenue, product, penetration and retention goals.
• Market and demand intelligence: Build a sharp, forward-looking view of the mortgage market, including origination volumes, refi and purchase cycles, lender share shifts, and segment dynamics across banks, independent mortgage banks (IMBs), credit unions and servicers. Translate it into forecasts and actions for the business.
• Revenue growth levers: Deliver analytics behind sales enablement, account planning, pricing, customer lifetime value, churn and white-space identification. Know which lenders are under-penetrated, where re-verification and servicing use cases can grow, and why.
• Product influence: Bring together industry trends, lender behavior and internal usage data to shape the product roadmap with Mortgage Product Management, including how our data supports GSE programs (e.g., Fannie Mae Day 1 Certainty®, Freddie Mac AIM) and lender automation.

2. Customer Co-Innovation & Data Products

• Trusted advisor to lenders: Partner directly with top mortgage lenders and servicers to solve their hardest problems, such as application to closed loan conversion rates, cost to close, cycle time, verification hit rates, fraud and early payment default risk. Use WS data to quantify the value.
• Executive storytelling: Turn complex analysis into compelling, executive-ready narratives, presentations and dashboards for lender C-suites, our sales teams and WS leadership.
• Productizing insight: Package WS data assets and recurring analyses into reusable, scalable, value-added products and services, such as benchmarking, portfolio insights and market intelligence, that create new revenue streams.
• Proof of value: Design and run pilots, ROI studies and lift analyses that show lenders the measurable impact of WS solutions and speed up deals.

3. AI-Powered Analytics at Scale

• AI-native operating model: Make AI the default way the team works. Use agentic workflows, LLM-assisted analysis and AI code-assist tools (e.g., Gemini, GitHub Copilot, Claude) to automate routine reporting, speed up insight generation and multiply team output.
• Conversational and self-serve insight: Partner with the AI/ML COE Leader to deploy secure, self-serve conversational analytics on Mortgage data, so sales, product and business leaders can get answers without waiting in a queue.
• AI-ready data products: Partner with the Data Platform Leader to make sure Mortgage data is modeled, governed and exposed through the semantic layer in ways that power both BI and AI use cases.
• Spot AI opportunities: Find where AI and ML can create new value for lenders, such as predictive demand signals, risk and fraud indicators, and next-best-action for sales, and bring those ideas to Product and the AI/ML COE.

Cross-Functional Leadership & Operating Model

• Mortgage business alignment: Operate as an extension of the Mortgage leadership team, maintaining structured cadence with Mortgage GM, Product, Sales, Marketing and Finance.
• D&A partnership: Work closely with the AI/ML COE Leader, the Data Platform Leader and peer Customer Analytics leaders. Reuse enterprise platforms and models rather than building one-off solutions.
• Responsible use of regulated data: Partner with Legal, Compliance and Privacy so all analytics and data products meet FCRA, permissible-purpose and fair lending requirements from the start.
• Talent and team building: Hire, develop and keep top analytical talent. Set a high bar for rigor, business acumen and AI fluency, and grow the team deliberately as value is proven.

What Experience You Need (Minimum requirements)

• Bachelor's Degree
• 10+ years in analytics leadership, including managing analytical consultants, data analysts, data scientists and/or data engineers
• Deep mortgage or consumer lending industry expertise, including the origination and servicing lifecycle, lender economics, GSE and secondary market dynamics, and the role of verification and credit data in mortgage decisions
• Proven record of embedding analytics in a business line and driving measurable revenue, penetration or retention outcomes
• Client-facing experience turning data assets into commercial products or services that generated revenue
• Hands-on experience applying AI (GenAI, LLMs, agentic tools, AI-assisted coding) to scale analytics and raise team productivity
• Strong executive presence, with the ability to simplify complex analysis into clear business recommendations for lender and internal C-suites
• Strong technical foundation in SQL and Python, plus modern BI and cloud data tools (GCP/BigQuery preferred)

What Could Set You Apart

• Master's or PhD in statistics, mathematics, economics, engineering or another quantitative field, or equivalent practical experience
• Experience working with FCRA-regulated or other sensitive consumer data
• Experience building self-serve or conversational analytics capabilities