Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Niche transport-economics specialization plus senior requirement reduces mass applicants, but metro location and desirable Python/SQL skills keep competition medium.
Role requires domain-specific transport/toll revenue expertise and investment-grade modelling, so background transferability across industries is low-high biased (high).
Explicit 8–12 years, investment-grade due diligence experience, and mandatory tech stack (Python, SQL, cloud, ETL) enforce high strictness.
Lead end-to-end economic modelling and forecasting for traffic due diligence and toll revenue projects.
Develop and validate advanced econometric and time-series models; oversee data pipelines and model governance.
Present technical findings and commercial recommendations to senior clients; manage small teams and contribute to business development.
Master’s degree in Economics, Econometrics, Transport Planning, Data Science or equivalent.
8–12 years of relevant experience including investment-grade traffic due diligence and toll revenue modelling.
Expert skills in Python (pandas, numpy, statsmodels, scikit-learn), advanced SQL (Postgres, BigQuery), and Advanced Excel.
Experience with data pipelines and tools (Docker, Airflow, Git, CI), and cloud analytics platforms (GCP/BigQuery or AWS).
Experienced in economic analysis and transport analytics with a focus on rigorous, investment-grade modelling.
Comfortable leading technical teams and client engagements while managing project timelines.
Skilled in translating complex quantitative analysis into clear, actionable commercial insights for senior stakeholders.