Lead Econometrics Modeler
Transurban - Full Time - Alexandria, Virginia
Working at Transurban is different; it's a place where you can see the benefits of your work play out in real life, every day. We create transportation solutions-building and operating safer, smarter, and more sustainable roads-to solve pressing transport challenges.
About the role:
We’re seeking a Lead Econometrics Modeler to develop Econometric and Machine Learning models for Transurban asset performance and pricing, and perform detailed data and statistical analysis to support activities within the business.
You’ll join an innovative team, who provides traffic forecasting and related services to support the management of existing assets and the development of new project opportunities in all geographies.
As our Lead Econometrics Modeler, you’ll contribute to lasting and positive changes that shape the future of our cities and communities. It’s meaningful, challenging and exciting work.
Day-to-day, you will:
Develop and maintain econometric models to support asset performance, pricing strategies, and market analysis.
Apply advanced analytics and machine learning to uncover trends in traffic and consumer behavior.
Lead statistical analysis of corporate and market data to inform business decisions and strategy.
Support the development of the Dynamic Tolling algorithm and dynamic pricing initiatives by building predictive algorithms and evaluating pricing impacts.
Contribute to toll rate modelling and pricing optimization to enhance customer value and revenue performance.
Collaborate across teams, when needed, to ensure timely delivery of fit-for-purpose models and analytical tools.
Monitor and refine models based on market feedback and evolving business needs.
This role will suit someone with a curious mind and transferable skills and experiences, including:
Demonstrated experience in the development and application of statistical, econometric and machine learning techniques, for time series analysis and forecasting and pricing models.
Knowledge in the principles of dynamic systems and system identification for applications to dynamic pricing.
Proficiency in programming languages, in particular R, Python and SQL.
Well-developed numerical skills and demonstrated ability to manipulate large datasets accurately.
Ability to independently research, present and convey information clearly and concisely.
Commitment to high quality outputs, timely delivery, and customer satisfaction.