
Markets Quantitative Analyst, Off
- Hangzhou, Zhejiang
- Permanent
- Full-time
- Development, review, and documentation of front office models within different SSM business units
- Justifying modeling assumptions and model results to internal model validation group
- Preparation and delivery of engagement status updates to key stakeholders
- Workflow management to ensure deliverables are prepared according to their timelines
- Support model owner, in the execution of engagement-specific statistical/financial modeling and analyses, and in preparation of final model deliverables
- Support SSM Risk and Capital Optimization team on quantitative analyses related to monitoring, forecasting and remediation of risk and regulatory resources
- Collaborate with model owner in designing and implementing suitable and effective model ongoing monitoring plan including performance metrics, thresholds, and escalation plan
- Support SSM Model Risk senior analyst to develop comprehensive first line of defense documentation including model development, implementation, and ongoing monitoring documents
- Work with model owners and developers on updating models to meet requirements from internal model validation group
- Strong understanding of quantitative analysis methods in relation to financial institutions
- Advanced programming skills in at least one supported statistical programming environment (Python, R, or MATLAB), with intermediate programming skills in VBA and other languages. Java experience is a plus
- Knowledge of financial markets (securities lending, equities and derivatives, FX or electronic trading, etc.) is a plus
- A demonstrated ability to multi-task and operate in a fast-paced, deadline-oriented environment
- Strong verbal and written communication skills, with ability to articulate ideas, analysis and complex concepts effectively to individuals from various backgrounds and ability to facilitate discussions and resolve conflicts between various stakeholders with competing interests
- Graduate degree in a quantitative discipline (Financial Mathematics, Financial Engineering, Mathematics, Statistics, or a related field)
- 2 to 4 years of working experience in model risk field recommended