Data Scientist
Listed on 2026-07-30
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IT/Tech
Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Location
Charleston - 997 Morrison Drive, Suite 402
BusinessOur 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®.
Join a purpose-driven team where your work creates opportunity, sparks innovation, and helps families across the country feel truly at home.
Job DescriptionThis position is onsite at 997 Morrison Dr, Charleston SC
Primary Responsibilities:
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.
Skills&
Competencies:
Qualifications:
- Bachelor's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field.
- 3+ years of experience in data science, analytics, or applied quantitative work.
- 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.
- Experience with in 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.
Skills:
- Data Science & Machine Learning:
Solid working knowledge of statistical modeling, predictive analytics, regression, and core machine learning methods. - Problem Solving:
Ability to take a defined business problem, develop an analytical approach, and translate findings into clear, usable recommendations for business partners. - Excel & Ad Hoc Analysis:
Advanced Excel skills, including the ability to quickly turn around ad‑hoc data requests, build clear analyses, and summarize results for business partners such as Asset Management and Operations. - Programming:
Strong Python and SQL skills for building models and analyzing data, with hands‑on experience using common libraries (e.g., pandas, scikit‑learn). - Artificial Intelligence:
Baseline experience working with AI tools, including an understanding of prompts and prompt…
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