CIB Risk-Quantitative Research Job Description
CIB risk-quantitative research
provides technical support and analyses of, and monitor developments in, the financial markets, and specifically the intersection of regulation and policy with financial and securities markets.
CIB Risk-Quantitative Research Duties & Responsibilities
To write an effective CIB risk-quantitative research job description, begin by listing detailed duties, responsibilities and expectations. We have included CIB risk-quantitative research job description templates that you can modify and use.
Sample responsibilities for this position include:
Good understanding of financial derivatives including Greeks
Participate in support and further development of internal probability of default (PD) and rating migration models
Develop the risk engines for Basel 2.5 Market Risk RWA models [VaR-based Measure (VBM), Specific Risk (SR), Incremental Risk Charge (IRC), and Comprehensive Risk Measure (CRM)]
Understand existing Basel 2.5 Market Risk RWA models [VaR-based Measure (VBM), Specific Risk (SR), Incremental Risk Charge (IRC), and Comprehensive Risk Measure (CRM)] and perform comparisons between outcomes of existing (Basel 2.5) and new (FRTB) rules
Research and implement innovative approaches to improving the performance of our analytics libraries by enhancing algorithms, parallelizing, employing GPUs
Communicating with end users and colleagues in QR or technology about risk and PL requirements explaining and supporting the calculations
Develop the risk engines for Basel 2.5 Market Risk RWA models [VaR-based Measure (VBM), Stressed VaR-based Measure (SVBM), Specific Risk (SR), Incremental Risk Charge (IRC), and Comprehensive Risk Measure (CRM)], their RWA forecasting models as part of CCAR/DFAST, and next generation of Market Risk RWA – FRTB
Develop Linear Rates models and implement them in C++ and Python for pricing and risk management of Rates derivatives
Explain model behavior and predictions to traders and controllers, identify major sources of risk in portfolios, carry out scenario and benchmarking analysis, provide guidance / debug analytics
Perform and assist with live pricing and risk management of trades using a variety of tools and models
CIB Risk-Quantitative Research Qualifications
Qualifications for a job description may include education, certification, and experience.
Education for CIB Risk-Quantitative Research
Typically a job would require a certain level of education.
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:
Financial products
But is not a strict requirement
Financial derivatives
Bond markets
Allowance methodology
Basel II and III regulatory capital
Excel and VBA
Financial Engineering
Preferably in Commodities
Probability
Desired experience for CIB risk-quantitative research includes:
Strong software design and programming skills in Python
Degree or equivalent from top tier schools/programs in Mathematics, Mathematical Finance, Physics or Engineering
PhD or equivalent degree in Math, Math Finance, Engineering or Statistics
PhD or Masters in numerate discipline such as Physics, Engineering, Computer Science, Mathematics, Mathematical Finance
Exceptional Python development skills
Graduate degree in either computer science or a numerate subject
CIB Risk-Quantitative Research Examples
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CIB Risk-Quantitative Research Job Description
Job Description Example
Our growing company is looking to fill the role of CIB risk-quantitative research. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for CIB risk-quantitative research
- 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
Qualifications for CIB risk-quantitative research
- 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
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CIB Risk-Quantitative Research Job Description
Job Description Example
Our innovative and growing company is searching for experienced candidates for the position of CIB risk-quantitative research. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for CIB risk-quantitative research
- 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
Qualifications for CIB risk-quantitative research
- 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
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CIB Risk-Quantitative Research Job Description
Job Description Example
Our company is looking for a CIB risk-quantitative research. We appreciate you taking the time to review the list of qualifications and to apply for the position. If you don’t fill all of the qualifications, you may still be considered depending on your level of experience.
Responsibilities for CIB risk-quantitative research
- 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
Qualifications for CIB risk-quantitative research
- 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
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CIB Risk-Quantitative Research Job Description
Job Description Example
Our innovative and growing company is searching for experienced candidates for the position of CIB risk-quantitative research. Thank you in advance for taking a look at the list of responsibilities and qualifications. We look forward to reviewing your resume.
Responsibilities for CIB risk-quantitative research
- 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
Qualifications for CIB risk-quantitative research
- 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#
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CIB Risk-Quantitative Research Job Description
Job Description Example
Our innovative and growing company is looking for a CIB risk-quantitative research. Please review the list of responsibilities and qualifications. While this is our ideal list, we will consider candidates that do not necessarily have all of the qualifications, but have sufficient experience and talent.
Responsibilities for CIB risk-quantitative research
- 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
Qualifications for CIB risk-quantitative research
- 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