Sr Mgr, Data Scientist

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

GPS is Greystar’s asset performance platform — the system through which we measure, compare, and optimize performance across the world’s largest multifamily portfolio. We are building GPS into a true data science platform: one that doesn’t just report on the past, but predicts outcomes, prescribes actions, and sets the industry standard for how asset performance is understood and improved.

We’re seeking a Senior Manager, Data Science to lead the data science function embedded within the GPS product team. This is a hands-on leadership role: you will build models, lead a small team of data scientists and ML engineers, and work directly with Product, Engineering, and business stakeholders to ship intelligence into a product used by Greystar’s leadership, property managers, owners, and investors. Our team includes engineers, designers, and product leaders with experience from Google, Microsoft, Airbnb, Strava, Amazon, and more.

KEY RESPONSIBILITIES:

Build and Ship Predictive and Prescriptive Models

• Design, build, and deploy models that power GPS — including asset performance scoring, NOI forecasting, renewal probability, lease pricing optimization, and anomaly detection across portfolio KPIs.
• Develop benchmarking and comparative analytics capabilities that allow Greystar to measure any asset against the portfolio, the market, and historical performance.
• Build models that move GPS from descriptive reporting toward prescriptive intelligence: surfacing what to do, not just what happened.
• Own the full model lifecycle within GPS: problem framing, feature engineering, model development, validation, deployment, monitoring, and iteration.

Integrate AI into the GPS Product Experience

• Partner tightly with GPS Product and Engineering to embed data science outputs directly into the product — as scores, alerts, recommendations, and natural language insights.
• Design and implement LLM-powered features within GPS, including AI-generated asset summaries, conversational data exploration, and automated narrative reporting for owners and investors.
• Build and maintain feature stores and serving infrastructure that allow models to operate in real time within the GPS application.
• Define and track model performance metrics that tie directly to business outcomes: accuracy of forecasts, adoption of recommendations, and measured NOI impact.

Lead and Grow a Data Science Team

• Manage and mentor a team of 2–4 data scientists and ML engineers embedded in the GPS product organization.
• Set technical standards for the team: code quality, model documentation, reproducibility, and