- Recent graduates or final year students.
- 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 specialised 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.