Compliance Division- Surveillance Analytics- Quantitative Investment Strategies- Associate
- Job id
- Full/Part Time
Job Summary & ResponsibilitiesDepartment Summary:
The Surveillance analytics group, SAG, within Global Compliance is a niche team that plays a central role helping the firm to manage its reputational and regulatory risk. One such area of focus is the risk associated with Quantitative Investment Strategies (QIS) based models.
The risks range from integrity of alpha models, integrity of the data input to the models and tests written in support of the models. To address these risks, the Firm has established model standards that include independent verification and testing of the models.
Summary of the Role:
This individual will be joining as part of the model verification team. He/She will be responsible to not only understand and verify checks and integrity of the models but also to challenge the underlying assumptions and design decisions.
The team works closely with compliance management, Portfolio Managers, Strats and IT who build the investment models, and respective compliance/legal officers
The Individual will require covering the following:
• Understand the architecture, and processes of the investment model
• Evaluate the design and regression tests for Models and Data Integrity
• Perform Verification across the different investment models ( Alpha, Risk, Data )
• Make recommendations for changes where appropriate
• Work with Strats/IT to ensure appropriate changes are implemented and meet the control
Basic Qualifications• 2 - 5 years of experience
• Work experience in developing quantitative portfolio models is preferable
• General understanding of a wide range of financial products that are traded (Buy Side)
• Programming Skills – Object Oriented Programming, familiarity with Modeling Frameworks, Time Series Architecture and Databases
• General understanding of the regulatory environment and rules
• Design specific tests to assess impacts of model driven risks identified in the validation
• Bachelor or Masters in applicable field e.g. computational finance, quantitative finance, computer science, mathematics