Data Scientist

About Us — Piedmont Residential

Piedmont Residential is a trusted homebuilder headquartered in the Metro Atlanta region, dedicated to delivering high-quality homes and well-planned communities for individuals and families across North Georgia. We focus on constructing homes that offer long-term value, thoughtful design, and lasting durability. Our communities are strategically located to provide access to strong schools, recreation, and local amenities, ensuring an exceptional living experience for our homeowners.

We are committed to guiding homebuyers through every stage of the building and purchasing process with professionalism, transparency, and a strong emphasis on customer satisfaction. Piedmont Residential operates with the belief that a new home is both a financial investment and a foundation for everyday life, and we strive to create environments that support the needs and aspirations of the families we serve.

Through disciplined planning, quality craftsmanship, and a dedication to continuous improvement, Piedmont Residential remains focused on building communities that contribute positively to the broader region and uphold our long-standing reputation for integrity, value, and service.

Position Overview

Piedmont Residential is seeking a highly motivated Data Scientist to support the development of an advanced residential real estate analysis platform. This platform will integrate mapping, predictive modeling, and financial analysis to support land acquisition and housing development decisions.

The platform will feature a mapping interface and provide tools to:

• Estimate imputed lot prices for potential developments
• Determine target home price points based on market demand and supply.
• Model absorption rates of homes in subdivisions.
• Allow users to test assumptions (lot size, price point, absorption rate).
• Integrate outputs into discounted cash flow (DCF) and pro forma models.

In addition to working with existing data sources, the Data Scientist will also contribute to building proprietary datasets through field research, direct data collection, and industry engagement.

Responsibilities

• Collect, clean, and analyze residential real estate, demographic, and economic datasets.
• Develop predictive models for lot pricing, target home price points, and absorption rates.
• Build and maintain geospatial and mapping data pipelines and interfaces.
• Design and implement frameworks for scenario and sensitivity analysis.
• Integrate analytical outputs into financial models, including DCF and pro forma statements.
• Conduct field research and primary data collection to validate findings and strengthen proprietary datasets.
• Collaborate with product managers, engineers, and internal real estate experts to refine platform features.
• Monitor data quality and continuously improve model performance.
• Document methodologies, assumptions, and research outcomes for internal stakeholders.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, or related field.
• 2+ years of experience in data science, applied analytics, or predictive modeling.
• Proficiency in Python, R, or a comparable programming language.
• Strong knowledge of SQL and data management principles.
• Familiarity with data visualization and geospatial tools.
• Experience applying machine learning and statistical methods to real-world datasets.
• Strong analytical, communication, and problem‑solving skills.
• Ability to conduct structured research, including fieldwork.

Preferred Qualifications

• Experience with real estate, housing, or financial datasets.
• Familiarity with DCF analysis and pro forma modeling.
• Exposure to cloud environments (AWS, GCP, Azure).
• Experience with interactive dashboards or applications (Tableau, Power BI).
• Background in survey design, primary data collection, or field research.