Data Scientist

About the role

• Location
• Charleston - 997 Morrison Drive, Suite 402
• Business
• Our Growth, Your Opportunity

At Maymont Homes, our success starts with people, our residents and our team. We are transforming the single-family rental experience through innovation, quality, and genuine care. With more than 20,000 homes across 47+ markets, 25+ build-to-rent communities, and continued expansion on the horizon, we are more than a leader in the industry-we are a company that puts people and communities at the heart of everything we do.

As part of Brookfield, Maymont Homes is growing quickly and making a lasting impact. We are also proud to be Certified™ by Great Place to Work®, a recognition based entirely on feedback from our employees. This honor reflects the culture of trust, collaboration, and belonging that makes Maymont a place where people thrive.

Join a purpose-driven team where your work creates opportunity, sparks innovation, and helps families across the country feel truly at home.

Position Summary

Requires being fully onsite - Charleston, SC

The Data Scientist leverages advanced analytics, statistical modeling, machine learning, and AI to solve complex business challenges and enable data-driven decision-making across the organization. This role develops, validates, and deploys predictive and statistical models using Python, while also performing hands-on data analysis, data extraction, and ad hoc reporting using Python, SQL, and Excel.

Working closely with cross-functional business partners, the Data Scientist translates business questions into analytical solutions, delivering actionable insights that support strategic initiatives and operational decision-making. The role is responsible for owning the end-to-end modeling lifecycle, including problem definition, data preparation, model development, validation, performance evaluation, and communication of results to both technical and non-technical audiences.

The ideal candidate combines strong expertise in data science, machine learning, and statistical analysis with practical proficiency in Python, SQL, and Excel. They are intellectually curious, analytical, and comfortable working with complex datasets to uncover meaningful insights. Success in this role requires the ability to quickly develop domain expertise in the housing industry, collaborate effectively with business stakeholders, and translate technical findings into clear, impactful recommendations that drive business value.

Essential Job Functions

• Partner with business teams, including Asset Management and Operations, to handle ad hoc data requests and support day-to-day operational and portfolio questions.
• Build predictive models in Python to address defined business problems, such as pricing, occupancy, or operational performance, in collaboration with senior team members.
• Help deploy models into production and monitor their performance, learning production best practices with support from senior team members and Data Engineering.
• Summarize findings into clear, concise takeaways for business partners.
• Collaborate with Data Engineering to ensure scalable, reliable, and trusted analytical datasets.

Performance Expectations & Key Metrics

• Decision Support: Provide timely, accurate analysis and ad hoc data support that helps business partners make better decisions.
• Model Building: Build and maintain models in Python that reliably address the business problems they are assigned to solve.
• Quality of Analysis: Deliver accurate, well-organized analyses that business partners can trust and use.
• Growth & Learning: Steadily expand technical skills and business knowledge, including new tools and modeling techniques and the housing industry, over time.
• Data Quality & Analytical Standards: Ensure analytical rigor, statistical integrity, reproducibility, and documentation across all models and analyses.

Required Qualifications

Education

• Bachelor's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field.

Experience

• 3+ years of experience in data science, analytics, or applied quantitative work.

Skills & Competencies

• Strong problem-solving skills and attention to detail.
• Strong Python, SQL, and Excel skills, with the ability to handle ad hoc data requests from business partners.
• Excellent communication, collaboration, and presentation skills with both technical and business audiences.
• Familiarity with Git, Agile development methodologies, and collaborative software development practices.

Preferred Qualifications

• Experience within real estate, private equity, investment management, asset management, or financial services.
• Experience building and deploying predictive pricing, forecasting, or optimization models in production.
• Experience utilizing geospatial analytics and external market data sources.
• Experience with AWS cloud services and modern AI platforms.