Top Remote Real Estate Data & Analytics Jobs

The Sr. Data Analyst will deliver actionable insights to stakeholders, develop predictive models, and support data-driven growth by analyzing diverse datasets.

Design, build, and operate secure, scalable cloud data pipelines, data lake/warehouse solutions, and governance. Integrate new sources, support analytics and BI, mentor junior engineers, enable data accessibility, and provide production support.

Lead Advanced Analytics to support product and business leaders at Airbnb; provide data insights, recommendations, and drive analytics strategies using A/B testing and metrics design.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

The Data Modeler is responsible for designing and maintaining data models, performing data profiling, supporting BI initiatives, and ensuring governance alignment.

Design and implement scalable data solutions, ETL pipelines, and integrations using Databricks and Azure, ensuring data quality and compliance for analytics.

The Workday Finance Reporting Analyst is responsible for designing, building, testing, and deploying Workday reports, analyzing functional specifications, providing troubleshooting support, and training users on Workday reporting functionality.

The Workplace Strategist will conduct research and data analysis to develop workplace strategies, create reports, and contribute to thought leadership in workplace trends.

Lead a small analytics team to evaluate and improve multifamily portfolio financial and operational performance. Build dashboards and financial models, define KPIs, assess capital and redevelopment impacts, and present actionable recommendations to senior leadership while partnering with Operations, Redevelopment, Finance, and Technology.

As a Data Analyst, you will build dbt models in Redshift, maintain data pipelines, and provide insights to enhance customer decisions while collaborating with internal teams.

Design and deploy ML and NLP models (including LLM evaluation) to predict borrower risk and property valuations, advise business teams, mentor junior analysts, and foster data-driven experimentation.