| Requirements |
- Recent graduates or final year students from disciplines relating to Mathematics, Statistics, Econometrics, Engineering or other degrees with a strong quantitative component.
- Should desirably have knowledge of modeling techniques (logit, GLM, time series, decision trees, random forests, clustering), statistical programming languages (SAS, R, Python, Matlab) and big data tools and platforms (Hadoop, Hive, etc.).
- Solid academic record.
- Strong computer skills.
- Postgraduate studies and/or specialized courses are an asset, especially in Data Science, Quantitative Finance or similar.
- Knowledge of other languages is desirable.
- Get
- up
- and
- go attitude, maturity, responsibility and strong work ethic.
- Strong ability to learn quickly.
- Able to integrate easily into multidisciplinary teams.
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