Senior Econometric Forecasting Lead - CRE Analytics

Visual Lease; Richmond (VA); On-site; USD 138,000 - 235,000; Full time

Benefits offered by this job

Healthcare package

401(k) retirement plan with matching

Job summary

CoStar Group in Richmond, VA seeks an Econometric Forecasting Lead to own and enhance commercial real estate forecasting models. You will collaborate with product, research, and quantitative analytics teams to improve offerings and ensure models remain robust and reliable.

The role requires a strong background in econometrics, time series, and large data handling, with senior-level experience and proven ability to explain complex methods to non-technical stakeholders.

Qualifications

• Master's degree in econometrics, statistics, data science, or related field from an accredited institution.
• 5-7+ years of relevant experience in econometric modeling, quantitative analytics, or commercial real estate forecasting.
• Proficiency in SQL, R, Python for data manipulation, analysis, and modeling (Stata a plus).
• Expertise in econometric models including regression, time series forecasting, and advanced techniques.

Responsibilities

• Monitor forecast accuracy using defined metrics and provide regular reports on back-testing.
• Collaborate with analytics to develop dashboards tracking forecast accuracy for leaders and executives.
• Refine inputs and coefficients to improve precision of forecasting models.
• Lead development of new forecast models for specialty CRE sectors and nowcasts.
• Document forecast models and methodologies clearly and educate the team on updates.

Skills

SQL

R

Python

Stata

Education

Master's degree in econometrics, statistics, data science, or related field

PhD (preferred) in econometrics or related field

Tools

Jupyter Notebooks

Numpy

Pandas

Scikit-learn

AWS

Azure

Job description

CoStar Group in Richmond, VA seeks an Econometric Forecasting Lead to own and enhance commercial real estate forecasting models. You will collaborate with product, research, and quantitative analytics teams to improve offerings and ensure models remain robust and reliable.

The role requires a strong background in econometrics, time series, and large data handling, with senior-level experience and proven ability to explain complex methods to non-technical stakeholders.