Econometric Forecasting Lead
CoStarGroup
Econometric Forecasting Lead Job Description OVERVIEW CoStar Group (NASDAQ: CSGP) 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. This is a full-time in-office position that will be based in our Richmond, VA office. 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.
- Continually 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.
- 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 years of 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.
- 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.
- 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
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