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Maymont Homes in Charleston, SC is seeking a Data Scientist to leverage Python, SQL, and Excel to build predictive models and deliver data-driven insights across asset management and operations.
The role owns the end-to-end modeling lifecycle, from problem definition to deployment and performance evaluation, and requires strong communication skills to translate technical findings for business audiences.
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.
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.
Our Growth, Your Opportunity At Maymont Homes, we’re committed to delivering an exceptional single-family rental experience shaped by innovation, quality, and genuine care for our residents. As a full-service acquisition, renovation, and property management company with a rapidly growing portfolio of approximately 20,000 homes and more than 25 build-to-rent communities across 47 markets nationwide, we blend advanced technology with a personal, people-first approach to create homes and experiences that truly stand out. It all starts with our people. Guided by values that champion excellence, collaboration, and innovation, our team members bring heart and purpose to everything they do. Together, we offer more than homes as we build trust, belonging, and better living opportunities for our residents across the country. We’re proud to be Certified™ by Great Place to Work®, a recognition based entirely on feedback from our employees. It reflects the inclusive, supportive, and high-performing culture that makes Maymont Homes a place where exceptional team members feel at home. At Maymont Homes, we’re creating better living opportunities and lasting impact for both our residents and our team members because when our people thrive, we thrive.