Description
A career as a Senior Data Scientist in the Transformation Unit of the Risk Modelling and Strategies (RMS) team It means helping to transform the RMS team's business capabilities by developing decision-making strategies that maximise the value of our new decision-making ecosystem and that bring gains on our performance indicators (automation/profitability/risk management).
Origination decision-making strategies are intended to automate the eligibility decision and credit limit assignment of credit applications based on data from View 360 and the credit bureau in order to optimise the Bank's capital allocation.
Your job:
- Develop statistical models and decision-making strategies for credit card origination.
- Draft the documents needed to approve their strategy
- Explain and influence partners (project squad, business line, risk management, it) in order to clearly communicate strategic recommendations.
- Work closely with the members of the RMS Transformation team to ensure the availability of explanatory data, the implementation of the algorithm in the decision engine, and the performance monitoring of decisions rendered.
Your team:
The RMS team is made up of 8 dynamic credit risk specialists with various profiles (Data Scientists, Data Stewards, Data Engineering Specialists, Business Analysts). As part of the large RMS team of more than 35 specialists in advanced analytics, we are a transformation unit responsible for implementing the target decision-making ecosystem for managing credit decisions. This includes setting up a data foundation for the target, integrating the new decision-making engine, and developing future models and strategies. You will report to the Senior Manager - Transformation - modelling and risk strategies.
Our goal is to offer you maximum flexibility in your work to promote your quality of life. This includes hybrid work in the office and remotely, working hours to reconcile work and personal life, and flexible leave at times that matter.
Prerequisite :
- Bachelor's or master's degree in a quantitative field, 2 to 3 years of modelling experience, decision-making strategies or any other relevant role in data science
- Proficiency in statistical/econometric models
- Business understanding of credit risk management
- Business understanding of the credit card product
- Proficiency in advanced analytics tools (Databricks, Snowflake, SQL/Python).