Capgemini is looking to unlock the value of technology and build a more sustainable, more inclusive world for the world's leading organizations
Requirements
- Experience using one or more programming languages (Python, R, C++, Java, Matlab, etc.)
- Manipulating data using SQL and Pandas
- Understanding of design, development and implementation of mathematical, financial risk and ML models
- Knowledge of advanced statistical techniques and concepts (regression, time series analysis, statistical tests, etc.)
- Python/R programming skills
- Data mining, data modelling and machine learning techniques
- JupyterHub/Python skills
Responsibilities
- Collaborate with stakeholders throughout the organization to develop project plans of delivering objects and timelines of model development and implementation
- Develop risk models in Python/R used by risk teams for regulatory stress testing submission and company risk management
- Design and build the execution workflow of models to forecast Balance Sheet, Fee Revenues, Macroeconomic Factors
- Coordinate with different functional teams to implement models and coordinate coding, testing, implementation and documentation of financial models
- Develop processes and tools to monitor and analyze model performance to ensure the expected application performance levels are achieved
- Apply data mining, data modelling and machine learning techniques to analyze large financial datasets and enhance the model performance
- Develop presentation decks using visual analytics tools and techniques
Other
- Master/MBA/PhD's Degree in a quantitative field (computer science, financial engineering, mathematics, data science or engineering)
- Excellent written and verbal communication skills for coordination across teams
- Relevant work experience in a related field based on education level
- Flexible work arrangements
- Paid time off and paid holidays
