Data & Business Analytics Analyst

Your Role and Responsibilities Analyze real estate market trends, property performance, and customer buying patterns to identify actionable insights. Develop and maintain dashboards and reports to monitor sales pipeline, inventory, customer engagement, marketing campaigns, and operational KPIs. Work closely with sales, marketing, finance, and operations teams to provide insights and recommendations that optimize business outcomes. Build models for property pricing analysis, customer segmentation, and demand forecasting. Conduct geospatial analysis using mapping tools to optimize site selection and territory planning. Analyze digital marketing and lead generation data to improve ROI on campaigns. Develop automated data pipelines and reporting tools to enhance efficiency. Present findings to leadership and support data-driven strategic decision-making. Required Technical and Professional Expertise Strong proficiency in SQL for data extraction and manipulation. Experience with Business Intelligence & Visualization tools (Tableau, Power BI, Looker, or similar). Ability to conduct market analysis, financial modeling, and forecasting. Familiarity with geospatial data and tools such as QGIS or ArcGIS is a plus. Knowledge of CRM platforms (Salesforce, Hubspot) and marketing analytics tools. Strong analytical mindset and problem-solving ability. Excellent communication and data storytelling skills. Qualification and Experience Required Bachelor’s or Master’s degree in Statistics, Data Science, Business Analytics, Economics, Real Estate, or related field. 1–3 years of experience in Analytics, Business Intelligence, or Data Analysis roles (Real Estate, Financial Services, or Consulting background preferred). Experience working with real estate data sources (internal property databases, external market feeds, digital marketing data). Understanding of real estate KPIs — sales velocity, inventory turns, pricing trends, lead-to-sale conversion. Experience with Python/R for data analysis is a plus. Familiarity with cloud data platforms (Google BigQuery, AWS Redshift, Snowflake) is a plus.