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Evening Real Estate Data Science Jobs (NOW HIRING)

This role will assist with real estate portfolio data management, reporting, project coordination, and real estate-related administrative processes across NOV's global portfolio of leased and owned ...

This role will assist with real estate portfolio data management, reporting, project coordination, and real estate-related administrative processes across NOV's global portfolio of leased and owned ...

Real Estate Specialist

Seattle, WA ยท Remote

$25 - $33/hr

Real Estate Specialist Duration : 6 months Location : REMOTE (8AM-5PM Seattle) Must-Haves ... Collaborate with engineers and data scientists to optimize model performance based on annotated ...

Real Estate Specialist

San Francisco, CA ยท Remote

$25 - $33/hr

Real Estate Specialist Duration : 6 months Location : REMOTE (8AM-5PM San Francisco) Must-Haves ... Collaborate with engineers and data scientists to optimize model performance based on annotated ...

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Evening Real Estate Data Science information

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$37.5K

$122.7K

$196.5K

How much do evening real estate data science jobs pay per year?

As of Jun 9, 2026, the average yearly pay for evening real estate data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is an Evening Real Estate Data Scientist?

An Evening Real Estate Data Scientist is a professional who applies data science techniques to analyze and interpret real estate data, typically working during evening hours. Their responsibilities often include examining property trends, evaluating investment opportunities, and creating predictive models to assist real estate companies or clients in making informed decisions. Working in the evenings can accommodate clients across different time zones or support organizations that operate outside standard business hours. These data scientists need strong analytical, statistical, and programming skills, often using tools like Python, R, and SQL. Their insights help optimize property valuation, marketing strategies, and operational efficiencies in the real estate sector.

What are the typical collaboration dynamics for an Evening Real Estate Data Science role?

In an Evening Real Estate Data Science role, you will often work closely with real estate analysts, property managers, and IT professionals to deliver data-driven insights outside of standard business hours. This unique schedule allows you to process and analyze large datasets with minimal interruptions while providing timely updates for teams starting their day. Regular communication is maintained via digital channels, and you may participate in virtual meetings or handoff sessions to ensure seamless workflow continuity. Collaboration is key, so strong remote communication and documentation skills are essential for success in this role.

What are the key skills and qualifications needed to thrive as an Evening Real Estate Data Scientist, and why are they important?

To excel as an Evening Real Estate Data Scientist, you need strong analytical skills, experience in statistical modeling, and a background in real estate, typically supported by a degree in data science, computer science, or a related field. Proficiency with tools like Python, R, SQL, and real estate analytics platforms such as CoStar or Zillow is essential, as well as familiarity with machine learning frameworks. Excellent problem-solving, communication, and time management skills help you translate complex data into actionable business insights, especially when working independently or on flexible evening schedules. These competencies are critical for providing accurate, timely analysis that supports strategic decision-making in the real estate sector.
What cities are hiring for Evening Real Estate Data Science jobs? Cities with the most Evening Real Estate Data Science job openings:
What are the most commonly searched types of Real Estate Data Science jobs? The most popular types of Real Estate Data Science jobs are:
What states have the most Evening Real Estate Data Science jobs? States with the most job openings for Evening Real Estate Data Science jobs include:
Real Estate Data & Automation Analyst

Real Estate Data & Automation Analyst

Stellar Management

Manhattan, NY โ€ข On-site

$75K - $85K/yr

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Real Estate Data & Automation Analyst
Department: Acquisitions
Employment Type: Full Time
Location: Corporate - New York
Compensation: $75,000 - $85,000 / year
Description
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.
Key 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.
Skills, Knowledge and Expertise
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.
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.
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.
Prior internship, coursework, or independent project work involving data scraping, automation, or applied machine learning preferred.
On-site presence required 5 days per week at the corporate office (44 West 28th Street, New York, NY).
Must be able to sit, stand, and walk for extended periods.
Capable of in-person, phone, and video communication with internal teams, outside counsel, vendors, and city agencies.