Overview
You will be working in key projects for leading organizations in data mining & knowledge discovery, predictive modeling, trend modeling, simulation models (Monte Carlo), review of credit rating and scoring models, and quantitative support to the business and R&D projects.
Responsibilities
- Contribute to data mining, predictive modeling, trend modeling, and Monte Carlo simulations as part of client projects.
- Support credit rating and scoring model reviews and provide quantitative input to business and R&D teams.
- Collaborate with multidisciplinary teams to translate business needs into quantitative analysis.
Qualifications
Recent graduates or final year students from disciplines relating to Mathematics, Physics, Statistics, Econometrics or other quantitative fields.Postgraduate studies and / or specialised courses are an asset, especially in Data Science, Quantitative Finance or similar.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 and strong computer skills.Knowledge of other languages is desirable.Get-up-and-go attitude, maturity, responsibility and strong work ethic, with the ability to learn quickly.Able to integrate easily into multidisciplinary teams.We Offer
Working in high-profile consulting projects for the largest companies, leaders of their markets, partnering with top industry management at national and global levels, as part of an extraordinary team of professionals with a benchmark corporate culture.Ongoing training with approximately 10% of business turnover spent on development.Specialist knowledge courses, external expert courses, professional skills courses, and language courses.Last year our staff as a whole received over 375,000 hours of training across more than 150 courses.Clearly defined career plan with internal promotion based on merit and a partnership-based management model offering opportunities to join the firm’s group of partners.Complementary experiences with university relationships, community / social initiatives, and sports activities.#J-18808-Ljbffr