Data Scientist
2 days ago
Description
About the Role :
We are seeking a highly skilled Data Scientist to join our data and analytics team, focused on delivering actionable insights across the commercial real estate (CRE) investment lifecycle.
You will develop predictive models, perform geospatial and statistical analysis, and deploy scalable AI/ML solutions that drive strategic decisions, asset valuation, risk mitigation, and portfolio optimization.
This role also includes building intelligent Agentic AI systems and RPA bots to automate analytical workflows, enhance underwriting, and streamline investment operations.
Ideal candidates bring a blend of ML expertise, CRE domain knowledge, and a passion for operationalizing real-world AI applications.
Key Responsibilities
Model Development & Forecasting :
- Build predictive models for rental income, lease renewals, occupancy, and property valuation.
- Develop risk models to assess exposure across locations, assets, and market cycles.
Data Integration & Analysis
- Perform EDA on lease, property, demographic, economic, and transaction data.
- Integrate data from ERP, CRM, and third-party sources (CoStar, RCA, CREXi, GIS).
Agentic AI & Automation
- Develop agentic AI bots using frameworks like LangChain Agents for autonomous analytics and task execution (e.g., market analysis, document parsing).
- Build and deploy RPA bots to automate data ingestion, reporting, and valuation workflows.
Visualization & Reporting
- Create automated dashboards using Power BI, Tableau for investment and asset teams.
- Communicate complex models and findings through clear, executive-level visualizations.
Model Deployment & MLOps
- Deploy models using APIs, Docker/Kubernetes, and cloud platforms (Azure ML, SageMaker, GCP)
- Automate pipelines for training, evaluation, monitoring, and drift detection using tools like MLflow and Airflow.
Governance & Best Practices
- Ensure data quality, model traceability, and compliance with ethical AI and privacy standards (e.g., GDPR, CCPA).
- Work in Agile teams and follow CI/CD and DevOps practices.
Education
Qualifications & Experience :
- Masters degree in computer science, Data Science, Statistics, or a related quantitative field.
Experience
- 5+ years in data science or machine learning, preferably in real estate, finance, or asset management.
- Experience with production-grade ML systems, automation, and agent-based AI solutions.
Soft Skills
- Strong business-first mindset with analytical depth
- Clear communication of technical insights to non-technical stakeholders
- Collaborative across investment, engineering, and finance teams
- Strong sense of ownership, prioritization, and ability to work in a fast-paced environment
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