ABOUT GREYSTAR

Greystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $300 billion of real estate in over 260 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing more than one million units/beds globally. Across its platforms, Greystar has over $79 billion of assets under management, including approximately $36 billion of development assets and over $30 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit www.greystar.com.

JOB DESCRIPTION SUMMARY

Greystar’s D2AI team is responsible for the platforms, processes, and practices that power AI across the organization. This role goes beyond traditional delivery—your decisions influence how data is transformed into intelligent, scalable solutions used by teams company‑wide. We require AI fluency because this role sits at the intersection of data, technology, and business outcomes. That means understanding how AI systems are designed and operationalized, using AI‑enabled tools in day‑to‑day work, and partnering effectively with engineering, analytics, and business teams to ensure AI solutions are reliable, responsible, and impactful.

In addition to your resume, all candidates are required to include a short video (2–5 min) demonstrating how you've used AI to improve your work — analysis, research, writing, process automation, or decision support. We recommend recording with Loom (free) or uploading as an unlisted YouTube video.

Please embed this link at the top of your resume. Applications without a video link will not be reviewed.

JOB DESCRIPTION

About the Role

Greystar is the world’s largest multifamily owner-operator, managing a portfolio that spans thousands of properties and billions in assets under management globally. Our proprietary data — spanning operations, leasing, investment, resident behavior, and market dynamics — is one of our most significant competitive assets. Today, we are building the organization, platform, and capabilities to turn that data into durable intelligence that drives every major decision across the company.

We’re seeking a Director, Data Scientist to serve as the senior-most data science leader at Greystar. Reporting to the Global Head of Data, Digital & AI, this Director-level role is responsible for setting the data science vision, methodology, and governance framework across the enterprise — and for ensuring that every AI and analytics initiative at Greystar is built on rigorous, trustworthy, and impactful science. This is not a research role. This is a leadership role for someone who builds systems that make an organization measurably smarter.

What You’ll Do

Set the Data Science Vision for Greystar

• Define Greystar’s enterprise data science strategy: where we invest in proprietary models, where we leverage vendor AI, and where we build reusable frameworks that serve multiple business units.
• Establish the methodological standards for data science across Greystar — including model development, validation, deployment, monitoring, and retirement.
• Identify the highest-value data science opportunities across USPM, Investment, Development, and Enterprise functions, and build a prioritized roadmap that ties directly to business outcomes.
• Serve as Greystar’s authoritative voice on data science to the OCEO, investors, partners, and the industry — translating technical capability into strategic advantage.

Build the Data Science Function

• Build and lead Greystar’s data science function, including direct management of centralized data scientists and dotted-line oversight of data scientists embedded in business units (e.g., the GPS Data Science team).
• Design the operating model for data science at Greystar: what is centralized (methodology, governance, platforms) vs. what is distributed (business-unit-specific modeling and analytics).
• Recruit, develop, and retain world-class data science talent in a real estate operating context — people who can build rigorous models and ship them into products that non-technical users depend on.
• Foster a culture of applied science: where models are measured by their business impact, not their complexity, and where shipping is valued over research.