The work that we do to meet our clients forecasting needs, and more generally, their modelling requirements, uses a specific set of statistical skills.
This includes not only descriptive statistics approaches and techniques but also crucially estimation methodologies and inference.
Amongst these are ordinary least square, generalized least squares, instrumental variables, structural break / unit root tests and cointegration.
In the end, our work adds value to EY clients by, first, analysing finate sample data sets, then, build models to explain change within the data, and forecast if necessary (whether in the time series or cross-sectional sense) and finally, develop and interpretation based on the models output, including the results statistical signifcance.
RESPONSABILITIES : Be involved throughout the project s cycle, i.e. initial model conceptualization, model development, model testing, output anlysis and reporting Develop the model in code using econometrics software Work closely with the project s managers to ensure that the work is delivered with quality and in time Work directly with the client as well as other EY teams Adapt our work to the clients expectations and requirements.
Identify potential risks in the projects conceptualization and execution phases, letting senior management know about these in time to resolve them Master s degree level in either Economics with a specialization in econometrics and / or statistics or Finance with a specialization in quantitative finance Familiarity with standard econometric models and methodologies such as ARIMAX, OLS, probit / logit / tobit models and VARs.
Knowledge of standard testing procedures, including general null-hypothesis testing, structural breaks, unit roots, auto-correlation and ideally endogeneity.
Thorough understanding of basic descriptive statistics methodologies, e.g. understanding and use of central tendencies, dispersions, histograms, correlations and ideally ANOVA Familiarity with standard probability distributions such as normal, log-normal, gamma, chi-square, etc.
Willingness to learn new models / techniques / methodological approaches, including by reading academic papers Coding experience in at least one of the following : R, STATA, Eviews, Matlab, RATS, C++ (can be flexible) Pay attention to detail at all time Be comfortable working with various quality control processes Be comfortable working with clients Be comfortable explaining technical issues (related to the models) both orally and in writing when asked