SeniorFull TimeEN
<br>
Job Description
<br>
CoStar Group (NASDAQ: CSGP) is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, CoStar Group is on a mission to digitize the world’s real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives.
We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our customers. We’ve continually refined, transformed and perfected our approach to our business, creating a language that has become standard in our industry, for our customers, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate.
Land.com
Land.com offers the largest and most effective marketplaces to discover, buy and sell rural real estate. The Land.com network connects millions of active buyers and landowners with the best local real estate professionals every month across three platforms.
Learn more about Land.com.
Role Description:
We are seeking a Senior Data Scientist to lead development and expansion of AcreValue’s predictive land valuation models and to help build the foundation for future AI-driven capabilities within the platform.
This role will focus primarily on expanding AV+ parcel-level land valuation and predictive modeling capabilities in collaboration with internal engineering and product teams.
The ideal candidate combines strong econometric and statistical modeling skills with geospatial data expertise, and can design models that are interpretable, defensible, and explainable to both technical and non-technical stakeholders. Equally important is the ability to independently research complex problems, investigate economic, geospatial, and environmental factors influencing land valuation, identify relevant datasets, evaluate modeling approaches, and translate findings into practical production models.
This role will work closely with engineering teams to operationalize valuation modeling workflows and scalable prediction processes, while contributing technical expertise toward the platform’s future AI initiatives, including natural language parcel search and AI-driven land insights.
This role is located in our Austin office and has a schedule of 5 days on-site.
Responsibilities:
Design, develop, and maintain parcel-level land valuation and predictive models used across the AcreValue platform
Research and expand valuation methodologies across diverse geographies and land types using geospatial, economic, and environmental data
Develop statistical and econometric models that are transparent, defensible, and explainable to both technical and non-technical stakeholders
Research land-use, economic, environmental, and geospatial factors influencing land values and incorporate findings into production predictive modeling approaches
Identify and prototype new datasets and model features prior to engineering implementation
Define and implement model evaluation, validation, and monitoring frameworks
Partner with engineering teams to operationalize valuation modeling workflows models, including training, prediction generation, validation and retraining processes
Contribute to research, prototyping, and technical evaluation of AI-driven land intelligence capabilities
Basic Qualifications:
Bachelor's degree required from an accredited, not-for-profit, in-person college/university
A track record of commitment to prior employers.
Experience building statistical or econometric models in Python for real-world predictive applications
Experience working with large geospatial datasets and spatial data concepts, including vector and raster formats, coordinate systems, and spatial joins
Preferred Qualifications:
Advanced degree in Economics, Data Science, Agricultural Economics, Statistics, Geospatial Science, Applied Mathematics, or Computer Science
Experience with Python geospatial libraries such as GeoPandas, Shapely, GDAL, or Rasterio
Experience working with spatial databases such as PostGIS or MongoDB with geospatial queries
Experience with parcel data, land cover datasets, satellite imagery, or soil and cropland data layers
Background in agricultural economics, farmland valuation, or real estate valuation
Experience deploying data science or machine learning systems in cloud environments such as AWS
Familiarity with GIS tools such as QGIS
What’s in it for you?
When you join CoStar Group, you’ll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed.
We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training, and tuition reimbursement.
Our benefits package includes (but is not limited to):
Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug
Life, legal, and supplementary insurance
Virtual and in person mental health counseling services for individuals and family
Commuter and parking benefits
401(K) retirement plan with matching contributions
Employee stock purchase plan
Paid time off
Tuition reimbursement
On-site fitness center and/or reimbursed fitness center membership costs (location dependent), with yoga studio, Pelotons, personal training, group exercise classes
Access to CoStar Group’s Employee Resource Groups
Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks
We welcome all qualified candidates who are currently eligible to work full-time in the United States to apply. However, please note that CoStar Group is not able to provide visa sponsorship for this position.
#LI-CG1
#Land.com
<br>
CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing