CIB Risk-Quantitative Research Job Description
CIB Risk-Quantitative Research Duties & Responsibilities
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CIB Risk-Quantitative Research Qualifications
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Education for CIB Risk-Quantitative Research
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Employers hiring for the CIB risk-quantitative research job most commonly would prefer for their future employee to have a relevant degree such as Master's and Bachelor's Degree in Engineering, Physics, Computer Science, Mathematics, Finance, Math, Technical, Statistics, Graduate, Economics
Skills for CIB Risk-Quantitative Research
Desired skills for CIB risk-quantitative research include:
Desired experience for CIB risk-quantitative research includes:
CIB Risk-Quantitative Research Examples
CIB Risk-Quantitative Research Job Description
- Development and implementation of LDFX models and products
- Close interaction with the LDFX Trading desk
- Analyzing Market Data used for Market Risk calculations such as VaR across several asset classes
- Suggest and participate in continuous improvements to the process and infrastructure
- Working with stakeholders such as Market Risk Coverage, MRQR product specialist & Technology teams to ensure the operational control of the process and troubleshooting technical issues
- Participate in Projects relating to Control issues / enhancements for Market Data Quality Improvement
- Assist in the production of weekly scorecards distributed to several groups and senior management
- Running Market data Quality reports, Quarterly Beta review and analyzing the time series for all positions for on boarding into VaR
- Follow up on LOB Market Risk audit-related issues
- Impact analysis on VaR/SVAR
- Previous practical experience in solving machine learning problems using open-source packages (sklearn…)
- Advanced degree in data science, statistics, mathematics or similar quantitative discipline
- Knowledge of real time option pricing/volatility fitting
- Experience in developing signals for options trading
- Knowledge of C++/Python programming languages
- PhD, MS or equivalent degree from top tier schools/programs in Mathematics, Mathematical Finance, Statistics, Physics, or Engineering
CIB Risk-Quantitative Research Job Description
- Close interaction with the Emerging Markets Trading desk
- Implementing efficient and scalable distributed calculations of risk, model recommended hedges, and hedge effectiveness PL attribution and trade-level profitability using our proprietary system, Athena
- Expanding the universe of products our desk can trade and manage by unifying methodologies and implementations of calculations performed in Athena across lines of business
- Improving the information available to the desk when considering trades by implementing trade-supporting calculations in Athena which are more timely than existing calculations
- Communicating with end users and colleagues in QR or technology about requirements explaining and supporting the calculations
- Developing VaR models for Rates, Exotic & hybrid products, including VaR methodologies development, time series selection/data quality checks, implementation, VaR model performance analysis & testing
- Summarize and assess the performance, model behaviour and suitability of the VAR models/engines to particular products and portfolios
- Coordinate VaR methodology & implementation projects with Market Risk quants, FO quants, Market Risk functions, Risk and Valuation Control Groups
- Develop and implement alternative portfolio analysis, model performance metrics
- Writing the final document to be reviewed by the Model Review Group
- Developing common model risk metrics, monitoring and diagnostics
- Leveraging machine learning techniques for model risk anomaly detection
- Developing new models for benchmarking existing ones
- Helping drive requirements of the new model reporting framework
- Working closely with other QR groups to implement consistent model risk practices across the groups
- Participate in generating data or information in response to ad-hoc internal and external requests relating to model risk
CIB Risk-Quantitative Research Job Description
- Implementing calculations in our proprietary system, Athena
- Analyzing and improving the performance or our calculations
- Improving the efficiency and accuracy of our processes through automation
- Support production runs, analytical explains, improvements to the Regulatory Capital Models Approach (AMA), Stress Loss (CCAR/DFAST) models and supporting documentation
- Research, development and implementation of new initiatives of risk models in the operational risk space economic capital model, cyber-risk quantification
- Act as QROR liaison for Regulatory Capital and CCAR/DFAST models, interfacing with corporate operational risk, model review group, audit and corporate technology
- Previous experience as a Quantitative Analyst
- Strong software development
- Masters degree or equivalent degree from top tier schools/programs in Mathematics, Mathematical Finance, Physics or Engineering
- Strong graduate degree in a quantitative field (Mathematics, Physics, Statistics, Economics, or Computation Finance)
- Experience working in a quantitative research role for an electronic trading group is preferred
- Familiarity with quadratic/conic optimization tools and software is preferred
CIB Risk-Quantitative Research Job Description
- Understanding of trading and modeling of financial securities
- Experience in, or exposure to, model validation or model development
- Previous experience with formulation of Statistical models / hands-on implementation of Machine Learning neural networks is a plus
- Strong quantitative and numerical programming skills
- Python numerical programming experience
- Experience developing and measuring statistical models
- Working closely with other QR groups to onboard our various model analytics onto the new framework
- Liaising with Technology groups to integrate the Model Reporting framework with other systems
- Helping design and build out other tools and analytics for managing model risk
- Supporting the users amongst QR, Model Governance and other groups in using our systems
- Identify opportunities for (improved) automation of existing and new workflows
- Applied development experience in object-oriented languages, such as Python, C++, Java, C#
CIB Risk-Quantitative Research Job Description
- Masters or PhD degree in Applied Math, Physics, Economics (quantitative), Engineering or similar
- Candidate should possess a master or doctorate degree in quantitative finance or in a quantitative discipline such as mathematics, statistics, science or engineering with solid knowledge in quantitative finance especially derivative pricing
- Solid C++/Python programming skill is required
- Previous working experience in numerical study involving finite difference method, statistical inference, time series analysis, optimization is strongly desired
- Strong communication skill is required
- PhD or equivalent degree in Mathematics, Mathematical Finance, Physics or Engineering, with strong Maths
- Knowledge of Mathematical Finance theory
- Knowledge of Commodity Option payoffs and pricing models
- Experience with programming in scripting languages (Python, R, Matlab) or C/ C++
- Knowledge of standard numerical methods and algorithms
- Undergraduate or graduate degree (preferable) and experience in mathematics or physical sciences or computer science or a quantitative discipline
- Experience in wholesale credit risk is a plus