My client, a top tier investment bank based in London is looking for Quantitative Analyst/Data Scientist to join their Regulatory Compliance Analytics team. The team is responsible for developing descriptive analytics and predictive models to support the Regulatory Compliance function in the management and monitoring of customer conduct risks. You will play a significant part in delivering the conduct risk management agenda through data management and statistical analysis, establishing clear and robust conduct governance and oversight.
Support the definition and build out of the conduct risk framework
Extract and analyse data through the use of SAS software (or other data management tools) from core systems
Provide assurance, through quality analysis, that staff performance is being achieved using well-intended means to deliver good customer outcomes
Identify and understand the root cause of complaints, poor staff behaviour and other conduct issues
Develop predictive models using traditional statistical modelling or machine learning techniques
Ensure the provision and adoption, of high quality insight and recommendations to further enhance the customer experience and the management of conduct
Define compliance metrics and design / deploy MI dashboards to provide insight into customer conduct issues
Execute the assigned projects/ analysis as per the agreed timelines and with accuracy and quality
Complete analysis as required and document results and formally present findings to management
Adhere with all the applicable compliance policies (Data security policy, operational risk, Functional manual, Group Compliance Manual, Audit recommendations, Internal Control requirements, relevant regulatory guidelines etc.) and the bank's business standards as applicable.
Master/PhD in quantitative subject, including Statistics, Mathematics, Economics (with focus on Econometrics), Signal Processing
At least 3 years of working experience in relevant Analytics field either banking book credit risk analytics, marketing analytics or fraud analytics. Knowledge and understanding of conduct risk preferred.
Knowledge of statistical techniques and working experience in tools like SQL /SAS or Matlab is a must. Also open to Python, R, C++ programming.
Project based business knowledge. Ability to diagnose issues and resolve simple to moderately complex issues.
Good analytical thought process and aptitude for problem solving.
Should be adept in using MS Office with exceptional MS Excel Skills, knowledge of VBA is preferable.
Experience and Exposure to visualization technologies such as Qlikview/ Spotfire/ Tableau will be an added advantage