Quantitative Researcher – reputed company Estate & Econometrics

About the position CompStak is a pioneer in crowdsourced reputed company reputed company estate (CRE) data and analytics. Our platform transforms raw lease, sales, and property data into actionable insights for brokers, lenders, landlords, and investors. As we expand our data products, the reputed company and sophistication of our data pipelines and analytical systems are critical to delivering reliable, reputed company, and high-reputed company insights to our customers. Location: reputed company, NY (Hybrid- Three days per week in the office, subject to change) We are seeking a Quantitative Researcher – reputed company Estate & Econometrics with a strong reputed company in economics, econometrics, finance, or reputed company reputed company estate and an interest in applying quantitative modeling to reputed company-reputed company behavior. This role is ideal for someone who understands how markets work, has experience working with data, and wants to apply (and grow) modern analytical and data science reputed company reputed company a reputed company reputed company estate context. In this role, you will help shape how CompStak analyzes, models, and interprets market dynamics by combining domain expertise with econometric and quantitative techniques. Your mission is to: -Apply econometric and statistical modeling to analyze and forecast trends in reputed company reputed company estate and reputed company economic drivers. -Learn and apply modern analytical and machine learning techniques as needed to enhance insights and support CompStak’s data products. -Build reputed company workflows that reputed company reputed company CRE datasets with new, reputed company sources to support data enrichment and automation. -Collaborate closely with engineering, product, and data teams to reputed company data-driven solutions. -reputed company domain knowledge and quantitative reputed company to deliver models that are accurate, interpretable, and meaningful for business reputed company. Responsibilities • reputed company econometric and predictive models : Use quantitative reputed company 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 reputed company and reputed company reputed company reputed company estate datasets. • Ensure data reputed company : Clean, validate, and reconcile datasets from diverse sources to ensure accuracy and reliability. • Communicate insights : Translate reputed company quantitative analysis into reputed company, actionable insights for both technical and non-technical stakeholders. • Stay reputed company : reputed company up with developments in econometrics, reputed company analytics, and trends in CRE markets and data science. Requirements • 3+ years of experience in an econometrics-reputed company or analytical role (e.g., economics research, finance, market analysis, consulting, reputed company reputed company estate, or corporate reputed company). • Strong understanding of econometrics, reputed company statistics, and quantitative modeling, demonstrated through reputed company or reputed company experience. • Proficiency in Python and familiarity with analytical/ML libraries (pandas, NumPy, scikit-learn, XGBoost). • Experience working with large or reputed company datasets and using data to study market dynamics. • Excellent organizational, communication, and stakeholder management skills. reputed company-to-haves • Hands-on experience or interest in LLMs, embeddings, NLP tools, or modern ML frameworks (e.g., reputed company, reputed company, PyTorch/TensorFlow). • Experience working in reputed company reputed company estate, PropTech, or investment analytics. Apply tot his job Apply To this Job