Economist

1 day ago


Whitehall Greater London, United Kingdom Jobs in Science Full time

Economist – Data Policy Analysis Team (DSIT)

End of March 2026 initially with extension pending.

Upto £700 per day, via umbrella inside IR35

Hybrid, Whitehall, London.

We are looking for an experienced Economist to join the Digital and Data Policy Directorate’s analytical team, supporting a landmark study on business data use and productivity. This role is central to delivering microeconomic analysis of longitudinal survey panel data, informing government strategies to boost growth and productivity.
The economist will lead on econometric modelling and critique, applying fixed-effects time-series and cross-sectional regression techniques to validate models and ensure robust in-sights. You will work closely with senior analysts and act as a subject matter expert, advising on model design and interpretation, and translating complex findings into actionable insights for policy colleagues.

Key Responsibilities:

• Analyse and interpret longitudinal panel survey data to assess links between data use and productivity.
• Develop and critique econometric models, ensuring methodological robustness.
• Provide expert advice on productivity metrics and economic modelling approaches.
• Collaborate with a multi-disciplinary team and contribute to policy-focused reports.

Essential Skills & Experience:

• Strong grounding in economic theory and empirical modelling.
• Expertise in panel data econometrics, causal inference, and time-series analysis.
• Proficiency in advanced econometric tools (Stata, R, Python).
• Ability to communicate complex analysis clearly to non-technical audiences.
• Degree-level qualification in economics or related quantitative discipline (PhD preferred) or equivalent experience.
Desirable:

• Experience in productivity analysis and growth decomposition.
• Government or private sector microeconomics experience.
• Familiarity with emerging technology and digital/data policy areas.
• Coding experience in R and Python



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