Real Estate Data & Automation Analyst

Stellar Management•New York, NY

2d•Onsite

About The Position

The Real Estate Data & Automation Analyst will support the firm’s Acquisitions and Asset Management groups by building and maintaining the data infrastructure, scrapers, and internal tools used to evaluate investments, manage existing assets, and respond to regulatory matters. The Analyst will sit at the intersection of the firm’s deal team and its technology function, translating open-ended business questions into repeatable software-driven workflows. Under general direction from senior leadership in Acquisitions & Asset Management, the Analyst will be expected to write production-quality code, deliver reusable internal tools, and contribute to the firm’s broader effort to modernize its technology stack and integrate AI into day-to-day operations. The role provides regular exposure to Principals and senior management, and offers a holistic view of how the firm sources, underwrites, owns, and operates assets.

Requirements

Working proficiency in Python, including pandas and at least one HTTP / web-scraping library (requests, httpx, BeautifulSoup, Playwright, or similar).
Comfort with SQL and basic relational data modeling.
Familiarity with Git and standard developer practices, including version control and code review.
Strong written and verbal communication skills, with the ability to summarize technical findings for non-technical audiences across the firm.
A self-motivated, organized approach to work, with the ability to scope and execute on open-ended business questions.
Strong attention to detail and a commitment to high-quality, reproducible output.
Proficiency in MS Excel, PowerPoint, and Word.
Bachelor’s degree in computer science, software engineering, data science, or a related field required.
0–2 years of relevant experience; recent graduates encouraged to apply.

Nice To Haves

Demonstrated interest in real estate, urban planning, housing policy, or NYC zoning and rent regulation preferred.
Exposure to GIS / geospatial tools (QGIS, PostGIS, GeoPandas) and NYC datasets such as PLUTO / MapPLUTO helpful, but not required.
Experience with LLM-based workflows, including retrieval-augmented generation, embeddings, or structured extraction, helpful, but not required.
Familiarity with Yardi or other real estate operating systems helpful, but not required.
Prior internship, coursework, or independent project work involving data scraping, automation, or applied machine learning preferred.

Responsibilities

Build and maintain scrapers, pipelines, and internal datasets sourced from the NYC open-data ecosystem and adjacent providers, including DOB / DOB NOW, ACRIS, HPD, DOF, PLUTO, ZoLa, NYC Open Data, StreetEasy, and OCA court records.
Aggregate sales and listing comps, permits, violations, complaints, dockets, registrations, and ownership records on demand and in repeatable batches to support underwriting and asset management.
Develop screening tools that identify acquisition, conversion, and off-site opportunities by filtering on community district, ZFA, light and air, vacancy, and zoning overlays.
Translate one-off analyst requests into durable, documented tools that the broader team can reuse.
Support active regulatory and asset-management matters by tagging, aggregating, and reconciling permits, contractor invoices, IAI records, and renovation documentation across the portfolio.
Maintain organized, audit-ready libraries of permits, plans, and supporting documentation by asset and by unit.
Identify candidate workflows for AI / LLM integration — including document classification, lease abstraction, permit interpretation, and natural-language querying of internal data — and prototype and evaluate solutions.
Migrate recurring analyses away from ad-hoc Excel exports and toward versioned scripts, internal datasets, and dashboards that refresh on a schedule.
Document data sources, code, and tooling so that work persists beyond any single project or staffing change.
Coordinate with outside counsel, consultants, property management, and acquisitions team members on data and documentation requests as needed.
Other related data, automation, and analytical tasks as assigned.