Econometric Forecasting Lead

CoStar Group, Inc.; Richmond (VA); On-site; USD 138,000 - 235,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) matching

Tuition reimbursement

On-site fitness center

Stock purchase plan

Paid time off

Job summary

CoStar Group is seeking an Econometric Forecasting Lead to enhance forecasting models for commercial real estate. You will work with product, research, and analytics teams to improve accuracy and develop new models across sectors.

The role emphasizes rigorous quantitative analysis, documentation, and clear communication of results to stakeholders. Strong SQL, R, and Python skills are essential.

Qualifications

• Master's degree in econometrics, statistics, data science, or related field from an accredited institution.
• Track record of commitment to prior employers.
• 5–7+ years of relevant experience in econometric modeling, quantitative analytics, or CRE forecasting.
• Strong proficiency in SQL (SSMS/Databricks), R, Python; familiarity with Stata a plus.
• Expertise in econometric models, including regression, time series forecasting, and advanced techniques.
• Hands-on experience with large data sets and forecasting models.
• Strong understanding of CRE dynamics and forecasting challenges.
• Excellent communication skills for non-technical audiences.
• Proactive, organized, and detail-oriented.

Responsibilities

• Monitor forecast accuracy using metrics (RMSE, MAE) and report results.
• Support dashboards to track forecast accuracy and enable actionable insights for leaders.
• Refine inputs and coefficients to improve existing forecasting models.
• Conduct quantitative research to evaluate CRE models and data series.
• Lead quarterly forecast accuracy review with feedback from analysts and external factors.
• Develop new forecast models for specialty sectors, nowcasts, and space-level analytics.
• Document models and methodologies clearly, including inputs and variables.
• Educate analytics team on forecast updates and drivers.

Skills

SQL

R

Python

Stata

Econometrics

Time series

Communication

Detail-oriented

Initiative

Education

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

Tools

SSMS/Databricks

Python toolkits (NumPy, Pandas, Scikit-learn)

Job description

OVERVIEW

CoStar Group is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, CoStar Group is on a mission to digitize the world’s real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives. We have been living and breathing the world of real estate information and online marketplaces for over 35 years, giving us the perspective to create truly unique and valuable offerings to our Clients. We’ve continually refined, transformed and perfected our approach to our business, creating a language that has become standard in our industry, for our Clients, and even our competitors. We continue that effort today and are always working to improve and drive innovation. This is how we deliver for our Clients, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate.

ABOUT THE ROLE

We are seeking a highly skilled and results-driven Econometric Forecasting Lead to take ownership of enhancing and improving our commercial real estate forecasting models. The successful candidate will have a strong background in econometrics, statistical modeling, and commercial real estate, with expertise in improving forecasting accuracy, innovating new models, and refining existing processes. This individual will play a key role in our analytics team, working closely with product, research, and quantitative analytics teams to improve our product offerings and ensure our forecasting models remain robust and reliable.

RESPONSIBILITIES

• Monitor and track forecast accuracy using defined metrics (e.g., RMSE, MAE), providing regular reports on accuracy/back testing and serving up data points used.
• Work with the analytics team to serve up data for the development of dashboards to track forecast accuracy, making insights actionable for analysts, department leaders, and executives.
• Continuously explore new economic inputs and refine existing variables and coefficients to enhance the precision and accuracy of existing forecasting models.
• Conduct independent and creative quantitative research applied towards the evaluation, tracking, and improvement of CRE models, data series and estimations.
• Lead and refine the quarterly review process for forecast accuracy, incorporating feedback from analysts and external factors to improve models.
• Develop and innovate new forecast models for specialty real estate sectors, nowcasts, space-level analytics, and other emerging real estate markets.
• Maintain clear documentation on forecast models and methodologies, including explanation of inputs, variables, etc.
• Provide ongoing education to analytics team on forecast updates and drivers and forecast accuracy.
• Lead communication of forecast process, guidelines, results, and updates to external customers, including back testing and accuracy review.
• Assist customers with model validations.

BASIC QUALIFICATIONS

• Master's degree in econometrics, statistics, data science, or related field from an accredited, not-for-profit, in-person college or university.
• Track record of commitment to prior employers.
• 5-7+ years of relevant experience in econometric modeling, quantitative analytics, or commercial real estate forecasting.
• Strong proficiency in SQL (SSMS/Databricks), R, Python, for data manipulation, analysis, and modeling (proficiency in Stata a plus).
• Expertise in econometric models, including regression analysis, time series forecasting, and advanced statistical techniques.
• Hands-on experience working with large data sets.
• Proven experience in developing and refining forecasting models.
• Strong understanding of commercial real estate dynamics, market drivers, and forecasting challenges.
• Exceptional communication skills, with the ability to explain complex models to non-technical stakeholders.
• Highly organized with heightened attention to detail.
• Proactive and self-driven, consistently taking initiative to identify and implement improvements.

PREFERRED QUALIFICATIONS

• Advanced degree (Master’s, PhD) in econometrics, statistics, data science, or related field from an accredited, not-for-profit, in-person college or university.
• Experience with Python-based common data science tools such as Jupyter Notebooks, Numpy, Pandas, Scikit-learn, etc.
• Experience writing clean, reproducible, robust, and scalable analysis code.
• Familiarity with cloud platforms (e.g., AWS, Azure) and data migration processes.
• Experience in space-level analytics or granular building data modeling.

WHAT’S IN IT FOR YOU

When you join CoStar Group, you’ll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed. We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training and tuition reimbursement. Our benefits package includes (but is not limited to):

• Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug
• Life, legal, and supplementary insurance
• Virtual and in person mental health counseling services for individuals and family
• Commuter and parking benefits
• 401(K) retirement plan with matching contributions
• Employee stock purchase plan
• Paid time off
• Tuition reimbursement
• On‑site fitness center and/or reimbursed fitness center membership costs (location dependent), with yoga studio, Pelotons, personal training, group exercise classes
• Access to CoStar Group’s Employee Resource Groups
• Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks

We welcome all qualified candidates who are currently eligible to work full-time in the United States to apply. However, please note that CoStar Group is not able to provide visa sponsorship for this position.

BASE COMPENSATION

Base Compensation: $137,800.00 - $235,400.00 Annually

EEO STATEMENT

CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing. CoStar Group is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces. Included in the S&P 500 Index, CoStar Group is on a mission to digitize the world’s real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives. We have been living and breathing the world of real estate information and online marketplaces for over 37 years, giving us the perspective to create truly unique and valuable products and services. We’ve continually refined, transformed and perfected our approach to our business, creating a language that has become standard in our industry and for our customers. This is how we deliver for our customers, our employees, and investors. By equipping the brightest minds with the best resources available, we provide an invaluable edge in real estate. CoStar Group is committed to creating a diverse environment and is proud to be an equal opportunity workplace and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. CoStar Group is also committed to compliance with all fair employment practices regarding citizenship and immigration status. If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access www.costargroup.com/careers as a result of your disability. You can request reasonable accommodations by sending an email to [e-mail].