{"id":1558954,"url":"https://alion.io/job/greystar-director-data-analytics","title":"Director, Data Analytics","company":{"id":4551,"name":"Greystar","domain":"greystar.com","url":"https://alion.io/company/greystar","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":86,"open_postings":76,"ghost_share":0,"stale_share":0.566,"repost_share":0,"time_to_fill_p50_days":22,"computed_at":"2026-10-04T05:45:00Z"}},"role":"Analytics","role_family":"Analytics","seniority":"head","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chicago, United States","Atlanta, United States","Tampa, United States","Houston, United States","Raleigh, United States","Charlotte, United States","Charleston, United States","Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":114000,"max_usd":245000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":162},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"Great Expectations","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-09-30T00:00:00Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-04T22:25:21Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"ABOUT GREYSTAR\nGreystar 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 www.greystar.com.\nJOB DESCRIPTION SUMMARY\nGreystar'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.\nThis 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.\nAbout the Role:\nGreystar 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.\nThis 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.\nThe 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.\nThe 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.\nYou'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.\nJOB DESCRIPTION\nWhat You'll Do\nLead the Property Operations Pod\nShape 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.\nOwn 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.\nOwn delivery: sequencing, quality, and whether what ships actually gets used, within the priorities set across Decision Intelligence.\nGo 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.\nMake 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.\nIdentify 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.\nDefault 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.\nContribute to how the broader pod model works by sharing patterns, tooling, and lessons from the largest pod with the rest of Decision Intelligence.\nBuild and Grow the Team\nHire, develop, and retain the analytics engineers on your pod, across the ladder from interns and associates through senior individual contributors.\nApply and help sharpen the career path and performance standard for the discipline, including what good looks like at each level on your team.\nGrow the next generation of leaders on your pod, including senior engineers who can run workstreams and eventually lead pods of their own.\nSet and hold a high technical bar through design reviews, hiring calibration, and direct engagement with the work rather than status reporting alone.\nBuild a team culture where people ship quickly, raise problems early, and are honest about what is and is not working.\nPartner with Property Operations Leadership\nOperate 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.\nRepresent the pod's work to senior leadership across Greystar, including progress, trade-offs, resourcing needs, and results.\nMake 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.\nBuild the case for the model with evidence, using measurable operational savings and revenue opportunity rather than activity metrics.\nManage 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.\nSet the AI and Technical Standard\nSet the standard for how your pod uses AI, including AI coding assistants as core tooling, and make sure speed never comes at the cost of work the team cannot explain or defend.\nStay current on where AI tooling is changing what a small embedded team can deliver, and adjust how your pod works accordingly.\nPartner with data engineering and platform teams on the data foundation your pod depends on, and escalate effectively when it is not meeting the bar.\nOwn data quality and trust as a leadership responsibility. When the data underneath a decision is wrong, you are accountable for driving it to root cause across organizational lines.\nEnsure the team follows data governance practices including access controls, PII handling, and appropriate use of data in AI systems.\nWhat You'll Bring\nLeadership Experience\n8+ years in analytics, analytics engineering, data science, or a closely related discipline, including 3+ years leading teams.\nExperience building and running a high-performing analytics team, including hiring, developing, and retaining strong technical talent in a competitive market.\nA track record of analytics work that changed business decisions and produced measurable outcomes, not just delivered reports and dashboards.\nExperience partnering with senior business stakeholders as a peer, including navigating competing priorities across business units.\nComfort operating in a model where your team is embedded in the business but accountable through a central organization, including advocating for your business partners without breaking enterprise alignment.\nAnalytics and Technical Depth\nHands-on background in SQL, Python, and data modeling deep enough to be credible in a design review and to set a real technical bar.\nExperience with a modern lakehouse or warehouse platform, ideally Databricks, and a working understanding of what it takes to run one well.\nFluency with business intelligence tooling such as Power BI, Tableau, or Qlik, and a point of view on when a dashboard is the wrong answer.\nUnderstanding of experiment design, measurement, and the difference between correlation and causation, sufficient to hold the team to it.\nEnough breadth to know what your team should build, what it should adopt, and what it should hand to a platform team.\nAI Fluency\nGenuine, hands-on fluency with AI tooling, including AI coding assistants such as Claude Code, Cursor, or Codex. This role sets the standard, so it cannot be secondhand.\nA clear point of view on how AI changes the scope of what a small analytics team can deliver, and where it does not.\nUnderstanding of how LLMs and AI agents consume data, including what makes a data product reliable when an AI tool is the consumer.\nJudgment on AI governance: data provenance, appropriate scoping, and responsible use, including when to slow down.\nHow You Operate\nBuilder's bias to action: you push the team toward working products in front of real users rather than long-dated plans, and you model it yourself.\nHigh standard, clearly held: you are specific about what good looks like, and \"it runs\" is not the bar. Reliability and quality are.\nDirect and honest: you raise problems early, deliver hard feedback well, and tell leadership what is actually happening rather than what is comfortable.\nYou learn the business: you go deep on the domain, including real estate, property management, investment, and financial data, and you expect your team to do the same.\nScope-disciplined: you protect the team from sprawl, say no with a reason, and keep the pod focused on work that matters.\nYou build people: you measure yourself partly by who on your team gets promoted and who grows into leading others.\n\nPreferredExperience in real estate, property management, financial services, or asset management.\nExperience embedded with an operations-heavy business, ideally one with distributed field or site-level teams.\nExperience working alongside platform or product engineering teams to productionize and scale analytics work.\nExperience in a global organization with operations across multiple regions.\n\n Tools & Technologies\nYou will not be hands-on in this stack daily, but you need enough fluency to make good calls, review work credibly, and earn the respect of the engineers you lead.AI coding assistants (Claude Code, Cursor, Codex) as core team tooling.\nSQL, Python, dbt or similar transformation frameworks.\nDatabrick...","description_format":"text","description_chars":15089,"description_truncated":true,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Life insurance","Parental leave"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Real Estate","Residential Real Estate","Property Management"],"lifecycle":[{"event":"open","at":"2026-10-01T03:19:29Z"}],"visa":[],"liveness":{"score":62,"band":"ok","label":"Likely open","p_open":1,"p_active":0.622,"p_room":1,"age_days":4,"expected_fill_days":22,"reasons":["conf:1","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-04T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/greystar-director-data-analytics","json_url":"https://alion.io/job/greystar-director-data-analytics.json","meta":{"generated_at":"2026-10-05T01:53:38Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2477,"day_limit":5000,"remaining_today":2523,"minute_limit":60,"resets_at":"2026-10-06T00:00:00Z"}}}