AI-Driven Data Scientist for Real Estate Analytics

CoStar Group; United States; On-site; USD 71,000 - 116,000; Full time

Benefits offered by this job

Healthcare coverage

401K with match

Tuition reimbursement

On-site fitness center

Job summary

CoStar Group in Richmond, VA is seeking a Data Scientist to build enhancements to data quality and research processes, applying machine learning, AI, and statistical modeling to deliver business impact.

The successful candidate will collaborate with product, engineering, and research leadership to translate requirements into data-driven solutions, develop models, and deploy demos or visualizations for diverse audiences in a full-time, in-office role.

Qualifications

• Bachelor’s degree in computer science, data analytics, statistics, machine learning, or related field.
• 2+ years of ML/AI experience with statistical modeling and data preparation.
• Proficiency in Python and PyTorch; able to work with large, complex datasets.
• Excellent communication to non-technical audiences and cross-functional collaboration.

Responsibilities

• Develop and evaluate ML models to support research goals and data quality.
• Leverage AI models including vision and multi-modal approaches to improve processes.
• Experiment, validate, and ensure robustness and fairness of models.
• Collaborate with research, product, and engineering teams to translate requirements.
• Present outputs as deployed demos or visualizations for diverse audiences.
• Monitor performance and retrain models as necessary.

Skills

Python

ML concepts

Statistical modeling

Cross-functional teamwork

Education

BSc/BA in CS or related

Tools

PyTorch

AWS

Job description

CoStar Group in Richmond, VA is seeking a Data Scientist to build enhancements to data quality and research processes, applying machine learning, AI, and statistical modeling to deliver business impact.

The successful candidate will collaborate with product, engineering, and research leadership to translate requirements into data-driven solutions, develop models, and deploy demos or visualizations for diverse audiences in a full-time, in-office role.