The Economist Intelligence Unit (EIU) is a world leader in global business intelligence. We help businesses, the financial sector and governments to understand how the world is changing and how that creates opportunities to be seized and risks to be managed.
At our heart is a 50-year forward-looking global forecast of the majority of the world’s economies. We seek to analyze the future and deliver that insight through multiple channels and insights, allowing our clients to make better business, investment and policy decisions.
We’re changing, embedding alternate data sources such as GPS and satellite data into our forecasting, products will increasingly be tailored to individual clients, driven by some of the most innovative data in the market.
The EIU is recruiting for a lead data analyst with a background in econometric modeling/statistical analysis with some managerial experience, to work within the quantitative economics – an international team of data analysts, econometricians and data scientists – that is in charge of The EIU’s key economic data products and the statistical/econometric model assets that powers the forecast and analysis published in the EIU’s core offerings.
How will you contribute?
The ideal skills for this role are:
An advanced degree in statistics, mathematics, applied econometrics, applied economics, business economics or a related quantitative field
At least 4 years of proven experience in statistical analysis and applied econometric modelling, especially in any of the following areas;
Time series models - ARIMA,Vector Autoregression, Co-integration, Error Correction Models, IRF
Mixed effect, multilevel, hierarchical models
Unsupervised learning techniques like PCA and Factor Analysis
State space models like Dynamic Factor models (for applications like Nowcasting)
Ridge/Lasso/Net-Elastic Regressions
Logistic Regressions and similar classification models
Experience with machine learning models or estimating econometric models with ML elements, like cross validations and bootstrapping
Prior domain experience in macro forecasting, economics or financial research would be good to have
A minimum of 1 year of proven experience in people management, either in small teams or projects with multiple stakeholders, is essential
Prior experience in applications of empirical and non-empirical methods (structural/semi-structural) for the purpose of macroeconomic forecasting will be good to have
Proficiency in programming languages - R and Python is required
Advanced Excel skills – experience with formula auditing, manipulating and cleaning large data sets in excel, knowledge of advanced functions like VLookup/HLookup, Match, Offset, Index, Indirect, Nested If-Then-Else and similar
Proficiency with SQL, to query databases will be good to have
Excellent communication skills
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