VP, Analytics, Data Science & AI Data Enablement

Walker & Dunlop

2d•$220,000 - $260,000•Remote

About The Position

The VP, Analytics, Data Science & AI Data Enablement will lead Walker & Dunlop’s Business Intelligence, Analytics, and Data Science functions and advance the use of AI to analyze data and inform business decisions. The role sets the strategy for turning data into actionable insights, accelerating delivery, and expanding access to trusted information across the organization. It leads the development of modern analytics capabilities, consistent data definitions and governance standards, and reliable access to data for business users and AI tools. The VP connects analytics strategy with business priorities to make data-driven insights timely, consistent, and accessible. The role oversees business intelligence solutions, advanced analytics, predictive models, reporting modernization, and AI-assisted analysis, while partnering with business lines and WDTech teams to embed analytics into business workflows. It also leads analytics and data science leaders and teams, provides technical oversight, and communicates strategy and results to executive leadership and stakeholders.

Requirements

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
12+ years of experience in data analytics, business intelligence, applied data science, or a related field, including at least 7 years leading multiple teams.
Demonstrated experience developing and executing analytics strategies aligned with business priorities and measurable organizational outcomes.
Proven ability to improve analytics delivery, operational efficiency, and analytical quality.
Experience implementing machine learning models, predictive analytics, and AI-assisted analysis in production environments.
Demonstrated success recruiting, developing, and retaining high-performing analytics and data science teams.
Experience with cloud data platforms and cloud analytical databases.
Strong knowledge of statistical analysis, machine learning, and data modeling, with the ability to evaluate analytical quality and provide technical direction.
Working knowledge of business intelligence tools such as Power BI or Tableau, as well as SQL and Python.
Practical understanding of modern AI analysis tools, their applications, and responsible implementation and use.
Strong knowledge of data governance, data quality, access controls, and analytical standards.
Understanding of semantic layers, metric definitions, and business context needed for consistent reporting and AI-assisted analysis.
Strong strategic thinking and problem-solving skills, with the ability to translate business priorities into actionable analytics initiatives.
Excellent written and verbal communication skills, including the ability to explain complex analytical concepts and technical trade-offs to executive leadership, business stakeholders, and technical teams.
Strong leadership and relationship management skills, including the ability to influence decisions, build partnerships, and collaborate across business functions.
Ability to balance long-term strategic planning with technical oversight, operational priorities, and timely execution.
Strong sense of ownership and accountability, with a results-oriented approach and commitment to delivering measurable business value.
Ability to take ownership of work, take on challenges, acknowledge growth opportunities, and demonstrate patience when learning new processes.
Courtesy, respect, and thoughtfulness when working with colleagues and stakeholders.

Nice To Haves

Master’s degree.
Experience with AWS and cloud analytical databases such as Amazon Redshift or Snowflake.
Experience in commercial real estate, financial services, or capital markets.

Responsibilities

Set the vision and develop a phased roadmap for business intelligence, analytics, data science, and AI-assisted analysis aligned with W&D’s strategic priorities.
Establish an operating model for partnering with business lines to identify needs, prioritize initiatives, allocate resources, and deliver high-value analytics solutions.
Define and maintain standards for analytical quality, KPIs, business metrics, and reporting consistency across the organization.
Improve the speed and quality of analytics delivery by establishing performance targets, measuring results, and identifying opportunities for continuous improvement.
Oversee the development and delivery of business intelligence solutions, advanced analytics, and predictive models that support decision-making across capital markets, credit risk, servicing, sales, and other business functions.
Lead the modernization of reporting and analytics capabilities, transitioning legacy reporting to scalable, governed business intelligence solutions.
Enable business users to conduct AI-assisted analysis using governed data, with standards for accuracy, reliability, and appropriate use.
Partner with Product, Engineering, and AI Enablement teams to integrate data and analytics into business workflows, providing datasets, metrics, and analytical capabilities to support implementation and measure results.
Establish practices for testing, validating, and monitoring analytical and machine learning models while maintaining standards for data quality, governance, and access.
Lead the development and maintenance of shared business definitions, metrics, and semantic frameworks for consistent interpretation of data across reporting, analytics, and AI applications.
Make trusted business context and data definitions accessible to analysts, business users, and AI tools.
Partner with AI Enablement, Data Engineering, and Product leaders to maintain the data structures, knowledge resources, and retrieval approaches needed to support AI-assisted analysis.
Expand shared data definitions and analytical capabilities based on business priorities, reporting needs, and evolving demand.
Lead, coach, and develop analytics and data science leaders and their teams, establishing hiring and development plans aligned with organizational priorities.
Provide technical direction and oversight by reviewing analytical models, queries, dashboards, and methodologies.
Collaborate with Data Engineering and Product leaders to maintain reliable shared datasets, establish service expectations, and support infrastructure for analytics and AI applications.
Communicate analytics strategy, progress, performance, and business outcomes to executive leadership and key stakeholders in clear, actionable business terms.
Perform other duties as assigned.

Benefits

Discretionary bonus and stock compensation.
Up to 83% subsidized medical payroll deductions.
Competitive dental and vision benefits.
401(k) with match.
Pre-tax transit and commuting benefits.
Health and wellness program with cash rewards and resources.
Paid maternity and parental leave, as well as other family paid leave programs.
Company-paid life, short- and long-term disability insurance.
Health Savings Account and Healthcare and Dependent Care Flexible Spending Accounts.
Career development opportunities.
Volunteer hours and donation matching.