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Sustainability Initiatives
- Assist to identify and plan automation and innovation initiatives.
- Lead engagement with respective Section Heads and Department Head on specific automation initiatives.
- Lead and oversee the development of major initiatives from end-to-end. Acts as Lead Analyst in ensuring quality of data analysts deliverables throughout process and lifecycle of model / algorithm development from data collection, data structure, trends and pattern analysis, present information via data visualization, propose solutions and strategies to department operational challenges.
- Ensure assigned work complies with acceptable audit standards and within stipulated time frame
- Lead collaboration with requirement owners to understand automation/analytics objective, relevant processes and gather requirements. Ensure requirements are conveyed accurately to the development team.
- Proposing, developing and implement automation solutions and contribute to ensure its successfully implementation.
- To review and ensure documentation is in place to confirm and translate agreed business rules into functional requirement for development"
- Iteratively, validate output/outcome with requirement owners based on agreed initial requirements provided.
- Ensure changes as required by owners are refined accordingly.
- Review and feedback the outcome/output presentation in Visual Analytics/Dashboards, if applicable.
- Keep abreast of new changes or revision of business rules and applies into Analytics library; i.e. maintenance of analytics scripts, versioning controls
- Review and propose suitable advanced Data Analytics algorithm and/or data modelling
GCAD Development
- Assess the need for enhancement on knowledge portal
- Assess and propose TA standards / process documentation and audit programs enhancement based on latest subject matter & knowledge retention needs
- Identify requirements and execute approved enhancements with subject matter and content owners.
- Oversee completion of competency gap e.g. questionnaire development, assessment communication.
- Assess competency gaps reporting and propose gap areas to be addressed for management decision.
- To provide knowledge sharing where applicable
- Assist the Section Head and TA Department Head to prepare presentation materials to the Audit Committee and relevant Senior Management Committee.
- Assist in establishment and lead in implementation of TA Department and impacted GCAD process efficiency enhancement and knowledge maintenance initiatives
- Assist to identify challenges & root causes and contribute towards establishing solution for exceptions in follow up of outstanding audit recommendations and closure validation. Assess reasonableness of responses to exceptions
- Propose automation and innovative ideas and solution towards sustainability of TA audit practices
- To assist in providing knowledge sharing to the auditors & advisors within Technology Audit Department within the specialisation of subject matter for audit framework, control standards and testing approach and on-the-job advice. To assist in identifying suitable subject matter specialist within the team provide the advice / knowledge sharing.
- To participate in audit assignments to provide expertise or assistance in testing the controls, where related to the specialised subject matter
- Participate in maintaining CoE of specialised areas
Collaboration
- Communicate and interact with relevant PICs across GCAD and CIMB
- Responsible to be a team player and collaborate when working in a team.
Others
- Carry out any other responsibilities/tasks as assigned by the TA Department Head or Section Head from time to time
Additional good-to-have
- Recognised Degree in IT, Computer Science, Data Science or AI related disciplines.
- Qualifications such as Certified Information System Auditor (CISA), Certified Analytics Professional (CAP) will be an added advantage.
- 6-8 years of relevant experience in system development, databases, AI / Machine Learning development, data science/analytics or CAATS.
- Related experience or academic exposure in the areas of Data Science or Data Analytics
- Understanding of machine-learning
- Knowledge of R, SQL and Python; familiarity with Java or C++ is an asset
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
- Strong math skills (e.g. statistics, algebra)
- Problem-solving aptitude
- Excellent communication and presentation skills
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
- Proficient in coding and query languages such as Java, Python, R & SQL
- Strong analytical and problem solving skills
- Good communication and presentation skill
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