Quantitative Researcher - Real Estate & Econometrics
About the position Responsibilities • Develop econometric and predictive models: Use quantitative methods to identify patterns, forecast trends, and interpret economic relationships in CRE markets. • Build and optimize data workflows: Create and refine data ingestion and transformation pipelines for structured and unstructured commercial real estate datasets. • Ensure data quality: Clean, validate, and reconcile datasets from diverse sources to ensure accuracy and reliability. • Communicate insights: Translate complex quantitative analysis into clear, actionable insights for both technical and non-technical stakeholders. • Stay current: Keep up with developments in econometrics, applied analytics, and trends in CRE markets and data science. Requirements • 3+ years of experience in an econometrics-focused or analytical role (e.g., economics research, finance, market analysis, consulting, commercial real estate, or corporate strategy). • Strong understanding of econometrics, applied statistics, and quantitative modeling, demonstrated through academic or professional experience. • Proficiency in Python and familiarity with analytical/ML libraries (pandas, NumPy, scikit-learn, XGBoost). • Experience working with large or complex datasets and using data to study market dynamics. • Excellent organizational, communication, and stakeholder management skills. Nice-to-haves • Hands-on experience or interest in LLMs, embeddings, NLP tools, or modern ML frameworks (e.g., Hugging Face, LangChain, PyTorch/TensorFlow). • Experience working in commercial real estate, PropTech, or investment analytics. Apply tot his job