My client, a top international bank is looking to hire to 2 exceptional SAS specialists with knowledge statistical modelling to join their team Financial Crime Compliance Analytics team. You can expect to join a young, high performing and culturally diverse team. They are open to candidates with strong SAS programming skills from other domains in banking that have an interest to work in Financial Crime Analytics.
You role is to ensure that the team's existing and emerging risk assessment models are adequately monitored periodically to ensure they track within pre-agreed thresholds and metrics that fall in line with risk appetite of both FCC and the individual business segments. The role will be responsible for conducting the technical processes required to produce the periodical statistics, presenting them, further refining them, and recommending changes to models based on findings from the monitoring process itself.
Technically execute an industry leading capability to ensure that all models produced by FCC Business Risk Assessment including the CRA (Client Risk Assessment) and other models are managed and monitored through appropriate and defensible means.
Developing a robust, repeatable and transparent framework for managing and monitoring models. This includes the procurement of data from source production systems (if required), simulating and comparing, creating periodical MI and dashboards, designing new dashboards as required.
Suggesting model changes to production and test models based on observations obtained from the periodical monitoring process.
Ensuring data obtained from model source systems and model outputs feeding in to monitoring processes is accurate, robust and fit for purpose.
Playing a key part in regular and periodical CRA validation in accordance with the FCC BRA validation standards.
Good degree in finance, accounting, mathematics, or social sciences with excellent quantitative methodological skill
Strong aptitude for working with large data sets with experience in data handling, identify trends and proposing new or revised analytical approaches to discover anomalies within data sets
Data gap, ETL, Data Quality and Data Warehousing capabilities.
Excellent collaborative and stakeholder skills and a desire to work as a part of a high functioning team of financial intelligence specialists.
Strong oral and written communications skills and experience defending research findings.
Strong skills in SAS, SQL (or other equivalent tool), and preferably at least one other programming language.
All interests and enquiries to Noel, Nhuang@argyllscott.com