Director, Data Analytics

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 $350 billion of real estate in more than 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 over one million units/beds globally. Across its platforms, Greystar has nearly $79 billion of assets under management, including over $34 billion of development assets and over $36.5 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

JOB DESCRIPTION SUMMARY

Greystar's D²AI organization (Data, Digital, and AI) is responsible for the platforms, processes, and practices that power analytics and AI across the company. Decision Intelligence is the team within D²AI that turns that capability into better business decisions. The name is the mandate: we exist to make the company's decisions faster, sharper, and better informed, not simply to produce reports.

Instead of a central intake queue, Decision Intelligence organizes into small, forward-deployed pods: analysts and engineers who sit alongside one another, each pod devoted to a critical area of the business such as Marketing, Property Operations, Resident, or FP&A. Pods become a standing part of that business rather than a rotating project resource, and the best of what they build graduates onto shared platforms so a win in one area becomes a capability for the whole company. Decision Intelligence reports through Technology, but a pod's priorities and success are defined by the business it serves, not by the technology organization.

This role leads the Property Operations pod. Property Operations is the core of what Greystar does, spanning the on-site teams, property performance, and operational execution behind the largest apartment portfolio in the world. It is the largest and highest-stakes pod in the model, and the work directly affects how thousands of communities and the teams running them operate every day.

About the Role:

Greystar is building the data foundation that will power the most AI-advanced operator in global multifamily real estate. As Director of Decision Intelligence for Property Operations, you lead the pod embedded in that business and you are accountable for whether it changes how Property Operations actually runs.

This is a builder's leadership role, not a caretaker's. You'll be accountable for the quality and impact of everything your pod ships, for hiring and developing the people who ship it, and for the standard the team holds itself to. You'll report to the leader of Decision Intelligence, who sets priorities and allocates resources across all pods, and you'll make the case for what Property Operations needs within that process.

The work comes from two directions. Property Operations brings you the problems it already knows it has, and you and your pod surface the ones it has not thought to raise. Between you, that defines what the pod takes on. How it gets solved is yours: the approach, the design, and the technology are your team's call, and the creative latitude that comes with that is one of the better parts of the job.

The role sits in a real tension and you should want that. Your pod is embedded deeply enough that Property Operations treats it as its own team, while you stay accountable through Decision Intelligence so the company gets enterprise leverage rather than a set of disconnected analytics groups. You'll operate as a peer to Property Operations leadership, and you'll represent the pod's work to senior leadership across Greystar.

You'll also set the technical and AI standard for your team. We are an AI-forward organization, and we expect the leader of this pod to be genuinely fluent, not merely supportive: credible in a design review, opinionated about where AI tooling changes what a small team can deliver, and able to tell the difference between work that is fast and work that is fast and sound.

What You'll Do

• Shape what the pod takes on alongside Property Operations leadership. The business brings problems it already knows it has, and you and your pod surface the opportunities it has not thought to ask for yet. Between you, that defines the work.
• Own how the work gets done. The approach, the design, and the technology choices belong to you and your team, and we expect you to use that latitude rather than wait for direction.
• Own delivery: sequencing, quality, and whether what ships actually gets used, within the priorities set across Decision Intelligence.
• Go deep on Property Operations yourself. You cannot spot the opportunities the business has not raised without understanding how properties, on-site teams, and operational performance actually work.
• Make sure the pod behaves like a standing part of the business rather than a project team, including keeping products alive and improving after launch rather than handing them off and moving on.
• Identify and champion the products worth graduating onto shared platforms such as the Greystar Performance System (GPS), our platform for enterprise reporting, and Podium, our internally built platform for enabling and governing AI use. Partner with platform teams to get them there.
• Default to doing it right; when speed is genuinely required, make the call to ship a usable solution with a documented path back to the governed, certified standard.
• Contribute to how the broader pod model works by sharing patterns, tooling, and lessons from the largest pod with the rest of Decision Intelligence.

Build and Grow the Team

• Hire, develop, and retain the analytics engineers on your pod, across the ladder from interns and associates through senior individual contributors.
• Apply and help sharpen the career path and performance standard for the discipline, including what good looks like at each level on your team.
• Grow the next generation of leaders on your pod, including senior engineers who can run workstreams and eventually lead pods of their own.
• Set and hold a high technical bar through design reviews, hiring calibration, and direct engagement with the work rather than status reporting alone.
• Build a team culture where people ship quickly, raise problems early, and are honest about what is and is not working.

Partner with Property Operations Leadership

• Operate as a peer to Property Operations leaders, building a shared roadmap from both their stated priorities and the opportunities your pod surfaces, and pushing back credibly when the ask and the impact do not line up.
• Represent the pod's work to senior leadership across Greystar, including progress, trade-offs, resourcing needs, and results.
• Make the case for what Property Operations needs within the central prioritization process, and communicate honestly to your business partners when the answer is not yes.
• Build the case for the model with evidence, using measurable operational savings and revenue opportunity rather than activity metrics.
• Manage the expectation that the pod does not leave. Continuous iteration with the business is the commitment, and you own making that sustainable rather than overextended.

Set the AI and Technical Standard