Requirements
About the Role:
Market Trend Analysis: Analyzes and interprets data on real estate market trends, including property values, sales patterns, and demographic shifts, to provide actionable insights for strategic decision-making.
Predictive Modeling: Develops and implements predictive models to forecast future real estate trends, assess investment risks, and optimize asset portfolios for clients.
Work Experience:
Experience in Real Estate Data Analysis: At least 2-4 years of experience working in data analysis, specifically within the real estate industry, focusing on property markets, investment analysis, or real estate development.
Experience with Data Tools: Proficiency in data analysis software such as SQL, Excel, R, Python, or Tableau, with a proven track record of utilizing these tools to generate insights and reports relevant to real estate.
Experience with Predictive Analytics: Hands-on experience in building and implementing predictive models related to real estate, such as property valuation, market trend forecasting, and risk assessment.
Qualifications:
Educational Background: A Bachelor's degree in Data Science, Statistics, Real Estate, Finance, Economics, or a related field. A Master's degree in a plus.
Real Estate Knowledge: Strong understanding of the real estate market, including property valuation, market dynamics, investment strategies, and economic factors influencing real estate.
Certifications: Professional certifications in data analytics or real estate, such as a Certified Analytics Professional (CAP), Real Estate Data Analyst certification, or similar credentials, would be beneficial.