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.

Drive Enterprise AI and Model Governance

• Own Greystar’s model governance framework: model inventory, risk classification, validation requirements, monitoring standards, and audit readiness.
• Establish standards for responsible AI across the enterprise — including bias detection, explainability, fairness, and compliance with evolving regulatory requirements.
• Partner with IT, Legal, and Compliance to ensure data science activities meet security, privacy, and regulatory standards across all geographies.
• Evaluate and approve the use of third-party AI/ML tools and vendor models, ensuring they meet Greystar’s standards for accuracy, governance, and data handling.

Deliver High-Impact Intelligence Across the Business

• Lead the development of Greystar’s core predictive and prescriptive capabilities: asset performance scoring, investment risk modeling, demand forecasting, pricing optimization, and operational benchmarking.
• Partner with the GPS product team to ensure data science outputs are deeply integrated into the platform — not siloed reports, but embedded intelligence that drives daily decisions.
• Work with Investment and Development leadership to build data science capabilities for underwriting, portfolio optimization, market selection, and deal evaluation.
• Identify and develop new revenue and differentiation opportunities built on Greystar’s data — including data-as-a-product offerings for owners, investors, and the broader industry.

Shape Greystar’s AI Future

• Stay ahead of the curve on AI/ML advancements — including foundation models, agentic AI, and domain-specific AI — and translate those developments into practical Greystar applications.
• Partner with Engineering and Platform teams to ensure Greystar’s data infrastructure (DMP, Databricks, MCP) is optimized for data science workloads at scale.
• Advise the Global Head of Data, Digital & AI on build/buy/partner decisions for AI capabilities, providing rigorous technical evaluation alongside business case analysis.
• Represent Greystar externally as a thought leader in applied AI for real estate — at conferences, with investors, and in industry forums.

What You Bring

Data Science Leadership

• 12+ years of applied data science, ML engineering, or quantitative research experience, with at least 4 years in a senior leadership role (Director or equivalent) managing teams of 5+.
• Proven track record of building data science functions from the ground up or transforming existing analytics organizations into high-performing data science teams.
• Experience setting enterprise-level data science strategy and governance in a complex, multi-business-unit organization.
• Demonstrated ability to translate data science capabilities into measurable business value — not just model metrics, but revenue, cost, and decision quality impact.

Technical Depth

• Deep expertise across the ML spectrum: supervised/unsupervised learning, time series, NLP, optimization, causal inference, and deep learning.
• Strong hands-on skills in Python and the modern ML/AI stack; you can still review code, evaluate model architectures, and challenge technical decisions credibly.
• Significant experience with LLMs in production: prompt engineering, fine-tuning, RAG, evaluation frameworks, and responsible deployment.
• Experience building and governing MLOps pipelines: model training, experiment tracking, deployment, monitoring, and automated retraining.

Business and Strategic Acumen

• Experience operating as a senior technical leader who influences business strategy, not just executes on it.
• Comfort presenting to C-level executives, investors, and board members — making the case for data science investment in clear economic terms.
• Strong opinions on build vs. buy for AI capabilities, grounded in practical experience evaluating and integrating vendor tools alongside proprietary development.
• Understanding of how data science intersects with product management, data engineering, and software engineering — and how to build effective partnerships across these functions.

Domain Knowledge (Preferred)

• Experience in real estate, property management, asset management, or financial services is strongly preferred.
• Familiarity with asset performance analytics, portfolio optimization, risk modeling, or valuation methodologies.
• Experience building data products or intelligence platforms that serve external clients or investors (not just internal analytics).

Mindset

• Applied over academic — you measure success by business impact, not publications.
• Builder mentality — you’ve built teams and systems from scratch, not just inherited them.
• AI-first — you use AI tools in your own workflow and expect the same of your team.
• Intellectually rigorous but pragmatic — you know when a simple model shipped today beats a perfect model shipped never.

Tools & Technologies

• Python, SQL, Spark/Databricks for model development and data processing at scale.
• MLflow, Weights & Biases, or similar for experiment tracking and model governance.
• Azure ML, Azure OpenAI, or equivalent cloud AI/ML platforms.
• LLM APIs (OpenAI, Anthropic), vector databases, and agentic AI frameworks.
• Familiarity with data governance and catalog tools (Unity Catalog, Purview, or similar).

The salary range for this position is $155,000-$185,000 USD Annually

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Additional Compensation:

Many factors go into determining employee pay within the posted range including business requirements, prior experience, current skills and geographical location.

• Corporate Positions: In addition to the base salary, this role may be eligible to participate in a quarterly or annual bonus program based on individual and company performance.

• Onsite Property Positions: In addition to the base salary, this role may be eligible to participate in weekly, monthly, and/or quarterly bonus programs.

Robust Benefits Offered*:

• Competitive Medical, Dental, Vision, and Disability & Life insurance benefits. Low (free basic) employee Medical costs for employee-only coverage; costs discounted after 3 and 5 years of service.

• Generous Paid Time off. All new hires start with 15 days of vacation, 4 personal days, 10 sick days, and 11 paid holidays. Plus your birthday off after 1 year of service! Additional vacation accrued with tenure.

• For onsite team members, onsite housing discount at Greystar-managed communities are available subject to discount and unit availability.

• 6-Week Paid Sabbatical after 10 years of service (and every 5 years thereafter).

• 401(k) with Company Match up to 6% of pay after 6 months of service.

• Paid Parental Leave and lifetime Fertility Benefit reimbursement up to $10,000 (includes adoption or surrogacy).

• Employee Assistance Program.

• Critical Illness, Accident, Hospital Indemnity, Pet Insurance and Legal Plans.

• Charitable giving program and benefits.

*Benefits offered for full-time employees. For Union and Prevailing Wage roles, compensation and benefits may vary from the listed information above due to Collective Bargaining Agreements and/or local governing authority.

Greystar will consider for employment qualified applicants with arrest and conviction records.

Important Notice: Greystar will never request your banking details or other sensitive personal information during the interview process. Greystar does not conduct any interviews via text or messaging, and all communication will come from official Greystar email addresses (@greystar.com). If you receive suspicious requests, please report them immediately to AskHR@greystar.com.

ANTICIPATED CLOSING DATE

May 31, 2026

This date may be subject to change due to evolving business needs.