The ICM In-Business Quality Assurance function (QA) verifies that established standards and processes are followed and consistently applied. ICM Management uses the results of the quality assurance reviews to assess the quality of the group's policies, procedures, programs, and practices as relates to the management of wholesale credit risk. The results help management identify operational weaknesses, risks associated with the function, training needs, and process deficiencies.
Key responsibilities include:
- Support the In-Business Quality Assurance Head of Data Analytics to set the global strategy for and lead the implementation and ongoing delivery of a robust Data analytics and testing program for the Quality Assurance function as it relates to Wholesale Credit Risk (WCR) data governance
- Provide effective challenge on the design and operation of the data and credit processes within ICM and report any identified gaps and concerns on those through quarterly reports published to ICG senior management. Ability to query and clean complex datasets from multiple sources, to funnel into advanced statistical analysis
- Hands-on experience in designing, planning, prototyping, productionizing, deploying, maintaining, and documenting reliable and scalable data science solution.
- Deep and hands-on in deriving concrete insight from data and qualifying business impact.
- Develop processes and tools to monitor and analyse model performance and data accuracy
- Collaborate within IBQA teams and with QA Directors and provide them with analytics insights
- Provide oversight and guidance over the assessment of complex data related issues, structure potential solutions and drive effective resolution with stakeholders.
- Support WCR IBQA team to abreast of relevant changes to rules/regulations and other industry news including regulatory findings.
- Support WCR IBQA Voice of the Employee (VOE) as well as diversity and inclusion initiatives
- Travel (less than 10%)
Skills/Competencies:
Analytics and Business:
- Demonstrable experience of at least 7 years of data analytics, in innovation, modelling and analytics, internal audit, or similar functions at an investment or large commercial bank
- Good grasp of Wholesale Credit Risk and Counterparty Credit Risk Processes and organizational awareness, to evaluate findings identified through the Quality Assurance process, determine materiality, and partnering with business to drive sustainable remediation.
- Excellent communication skills with the ability to effectively collaborate with stakeholders at all levels to elicit requirements and priorities.
Leadership:
- Assists colleagues in identifying stretch opportunities to elevate individual and team performance and recognizes individuals based on performance.
- Continuous learning and improvement mindset.
- Coach, mentor, and lead team members to develop team strengths.
- Proven culture carrier
Competencies:
- Solid organizational skills with ability and willingness to work under pressure and manages time and priorities effectively.
- A logical and methodical mindset, strong analytical and problem-solving skills, with the ability to think critically, working with others to propose creative solutions.
- Leading the delivery of the areas of complex or judgemental QA work, including identifying issues, analysing multiple data points to draw informed conclusions and clearly articulate these conclusions in written and verbal form to senior stakeholders.
- Good interpersonal communication skills which will be required for both internal and external business partners.
- Attention to detail and a commitment to delivering high-quality work.
- A drive to learn and master new technologies and techniques.
- Experience in analysing datasets and distilling them into actionable information as well as building out end-to-end analytical process flows.
- Understanding of process redesign / re-engineering and execution
- Experience in preparing presentations for seniors.
Technical:
- Coding knowledge and experience with at least two programming languages (C++, Python, C#, Java, R, etc.).
- Experience with deep learning framework PyTorch strongly preferred but not mandatory.
- Experience working and manipulating large set of data.
Qualifications:
- Bachelor’s or Master’s degree in Maths Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
- Data Analysis: SQL; Python; SAS; R, Alteryx, Splunk;
- Visualisation: Tableau; Qlikview; MS Power BI.
- Programming language: Python, Java, C++,
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
Decision ManagementSpecialized Analytics (Data Science/Computational Statistics)
Time Type:
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