Senior Data Scientist
Austin, TX - USA
Job Summary
Job Description
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 worlds 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. Weve 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.
offers the largest and most effective marketplaces to discover buy and sell rural real estate. The network connectsmillions ofactive buyers andlandownerswith the best local real estate professionals every month across three platforms.
Learn more about.
Role Description:
We are seeking aSeniorData Scientistto lead development and expansion of AcreValuespredictiveland valuation models and to helpbuild the foundation for future AI-driven capabilities within the platform.
This role will focus primarily on expanding AVparcel-level land valuationand predictivemodelingcapabilitiesin collaboration withinternal engineeringand productteams.
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 investigateeconomic 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 tooperationalize valuation modeling workflows and scalable prediction processes while contributing technical expertise toward the platforms future AI initiatives including natural language parcel search and AI-driven land insights.
This role is located in ourAustinoffice and has a schedule of5days on-site.
Responsibilities:
Designdevelop and maintain parcel-level land valuationand predictivemodels used across the AcreValue platform
Researchandexpandvaluationmethodologiesacrossdiversegeographiesand land typesusing geospatial economic and environmental data
Developstatistical and econometric modelsthat are transparent defensible and explainable to both technical and non-technical stakeholders
Research land-use economicenvironmentaland geospatial factorsinfluencingland values andincorporatefindings intoproduction 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 tooperationalize valuation modeling workflows models including trainingprediction generationvalidationand retrainingprocesses
Contribute toresearch prototyping and technical evaluationof AI-driven land intelligencecapabilities
Basic Qualifications:
Bachelors 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
Whats in it for you
When you join CoStar Group youll 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 Groups 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 please note that CoStar Group is not able to provide visa sponsorship for this position.
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CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing
Required Experience:
Senior IC
About Company
The most recommended lease management platform for office and retail tenant portfolios of commercial real estate.