Description

• Develop and maintain quantitative risk analytics solutions using Python for financial risk technology.
• Design and implement systems for Value at Risk (VaR), Expected Shortfall (ES), and stress testing.
• Process and analyze large-scale financial time series data and market risk calculations.
• Enhance and optimize quantitative risk engines and data-processing workflows.
• Collaborate on projects related to market data, risk factors, and quantitative market risk analytics.
• Apply strong problem-solving, analytical, debugging, and performance optimization skills.
• Work with large datasets to ensure reliable and efficient data handling.
• (Preferred) Utilize knowledge of FRTB, CCAR, and exposure to cloud/big data technologies such as Azure, Databricks, Spark, or Kubernetes.
• Key focus: Hands-on Python expertise, experience in VaR/ES/stress testing, and handling financial time series data

Key Skills

Education

Bachelor's degree