Real Estate Data Analyst / Predictive Modeling Specialist
Part-time. Remote, applicants in the Philippines
About the role
We are looking for a skilled Real Estate Data Analyst / Predictive Modeling Specialist to help develop a data-driven model that analyzes real estate data and ranks properties based on defined criteria, market trends, and potential investment performance.
The ideal candidate has a strong background in data analysis, statistical modeling, and Python development, with the ability to transform raw property data into meaningful insights and actionable rankings. Experience with machine learning and predictive analytics is highly desirable.
Key Responsibilities
Analyze real estate data, including property prices, rental yields, market trends, property characteristics, and other relevant metrics.
Develop and refine a data model or property-scoring system to evaluate and rank properties based on specified criteria.
Collect, clean, validate, and organize data from multiple sources to ensure accuracy and consistency.
Use Python and relevant data analysis libraries to process large datasets and identify meaningful patterns.
Apply statistical methods and, where appropriate, machine learning techniques to assess property performance and investment potential.
Design and implement algorithms that generate property scores or rankings based on agreed-upon parameters.
Test, validate, and improve the model to ensure that its results are reliable and useful for decision-making.
Present findings, insights, and recommendations in a clear and understandable format.
Collaborate with the client to understand business objectives, refine ranking criteria, and improve the model over time.
Qualifications and Requirements
Proven experience in data analysis, data science, statistical modeling, or a related technical field.
Strong proficiency in Python, particularly with libraries such as Pandas, NumPy, and Scikit-learn.
Experience in developing analytical models, scoring systems, or predictive models.
Strong understanding of data cleaning, feature engineering, statistical analysis, and model…
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