Data Scientist

Data Scientist (Real Estate)

Location: Remote

Job Type: Full-time

About Us: Homely is a rapidly expanding Southern California-based start-up, offers you the chance to take control of your income and career. Our leadership team is seasoned in driving massive growth and investing in real estate—now we're looking for top-tier talent to help us scale. We are looking for a talented Data Scientist to join our team and drive innovation in the real estate industry through advanced analytics and machine learning.

Job Summary: The Data Scientist (Real Estate) will analyze large datasets, develop predictive models, and generate actionable insights to support investment decisions, pricing strategies, and market analysis. This role requires expertise in data science, machine learning, and statistical analysis, combined with an understanding of real estate market dynamics.

Key Responsibilities:

● Collect, clean, and analyze real estate data from multiple sources (MLS, public records, property listings, market reports, etc.).

● Develop machine learning models to predict property prices, rental values, and market trends.

● Identify trends in housing prices, rental rates, and demand. Predict future real estate trends using historical data and machine learning models.

● Analyze economic indicators like interest rates and employment rates to determine their impact on the real estate market. Build data-driven tools for investment analysis, customer segmentation, and risk assessment.

● Conduct geospatial analysis to identify high-growth real estate opportunities.

● Develop machine learning models to predict property prices based on location, square footage, number of bedrooms, and nearby amenities.

● Analyze comparables (comps) to set competitive pricing for sellers and landlords.

● Use AI-powered models to suggest pricing strategies for real estate listings.

● Automate data pipelines and dashboards to provide real-time market insights. Work closely with product, marketing, and finance teams to optimize real estate strategies.

● Detect and mitigate fraud risks using anomaly detection techniques.

● Research and implement AI solutions to enhance property recommendations and customer engagement.

● Evaluate investment risks by analyzing factors such as neighborhood crime rates, foreclosure rates, and economic stability.

● Detect fraudulent real estate transactions by identifying anomalies in buying patterns or mortgage applications.

● Assess creditworthiness of buyers using alternative data sources.

● Help investors identify high-return properties based on ROI (Return on Investment) and cap rates.

● Create predictive models to determine the best locations for property development.

● Use geospatial analysis to identify emerging real estate hotspots.

● Automate property management tasks like tenant screening, rent collection, and maintenance requests.

● Streamline real estate transactions by using AI-powered document processing.

● Optimize real estate listings for better engagement on digital platforms.

● Predict the impact of new developments on property values.

● Stay updated on industry trends, emerging technologies, and regulatory changes in real estate analytics.

Qualifications:

● Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Economics, or a related field.

● 2+ years of experience in data science, preferably in the real estate, finance, or proptech industries.

● Proficiency in Python, R, SQL, and data visualization tools (Tableau, Power BI, or similar).

● Strong understanding of machine learning algorithms, statistical modeling, and predictive analytics.

● Experience working with large datasets, cloud platforms (AWS, GCP, Azure), and database management.

● Knowledge of geospatial analysis (GIS) and real estate valuation models is a plus.

● Excellent problem-solving skills and the ability to translate data insights into business value.

● Strong communication skills and the ability to collaborate with cross-functional teams.

Compensation & Benefits:

● Competitive Salary

● US Federal Holidays: Paid time off.

● Payroll: Weekly

● Method of Payment (MOP): Deel

Work Schedule

● 9 AM - 6 PM PST, with 1 hr lunch. Monday to Friday

Job Type: Full-time

Benefits:

• Work from home

Application Question(s):

• Do you have hands-on experience developing and deploying machine learning models in a production environment? How long?
• Have you built predictive models for valuation, prices, or market trends?
• What programming languages and tools are you proficient in?

Work Location: Remote