Quantitative Research Associate - Asset and Wealth Management Risk

2 - 5 years

2 - 5 Lacs

Posted:3 months ago| Platform: Foundit logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Job Overview:

  • Exciting opportunity to join a dynamic, growing team in the Asset & Wealth Management Risk Team.
  • Partner with the Business to provide a comprehensive view on risk management.
  • Role involves developing and maintaining risk measurement methodologies and managing the Newton system, used by both Risk and Front Office stakeholders.

Job Responsibilities:

  • Contribute to research and enhancement of risk methodology (sensitivity, stress, VaR, factor modeling, Lending Value pricing for market, credit, and liquidity risk).
  • Collaborate with peers and stakeholders to identify opportunities for Data Science to add value.
  • Use knowledge of Computer Science, Statistics, Mathematics, and Data Science to provide insights into security and portfolio risk analytics.
  • Assist with continuous improvements in Machine Learning and statistical techniques for data and analytics validation.
  • Design and deliver flexible, scalable solutions using firm-approved tools.
  • Prepare model documentation for Model Risk Governance and Review group for validation, monitoring, and backtesting.
  • Contribute to the analysis of large data sets and assist with their onboarding using best practice data models and big data platforms.

Required Qualifications, Capabilities, and Skills:

  • 2+ years of experience in quantitative analysis/research, data science, Market/Credit Risk Management, or a Front Office role (or academic equivalent).
  • Detail-oriented, with strong multitasking and independent work abilities.
  • Excellent communication skills.
  • Strong understanding of statistics applied AI/ML techniques, and practical problem-solving mindset.
  • Practical experience in financial markets within Risk Management or Front Office roles.

Preferred Qualifications, Capabilities, and Skills:

  • Knowledge of asset pricing, VaR back testing techniques, and model performance testing.
  • Experience in modular programming with SQL, Python, ML, AWS Sagemaker, and TensorFlow.
  • Degree in a quantitative or technology field (Economics, Maths/Statistics, Engineering, Computer Science or equivalent).

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