The Senior Data Analyst is responsible for the development of data analytics techniques and other projects with little or no supervision from the Data Analytics Manager. The Senior Data Analyst is expected to apply well-developed knowledge and expertise across multiple software tools and platforms, have a high level of expertise in one or more software tools, perform thorough testing of analytics and document work performed in conformance with internal audit policies and procedures.
The Senior Data Analyst will regularly interact with the audit teams, as well as others in the lines of business. The ideal candidate will feel at ease querying databases, integrating data from multiple/disparate sources, conducting sophisticated quantitative analyses, and presenting their findings.
1.Developing complex data analytics routines across multiple platforms and tools.
2.Ensuring that analytic products support audit scope, provide sound conclusions, are fully tested, and are documented clearly, concisely and sufficiently to facilitate re-performance.
3.Collaborating with the Corporate Audit Services (CAS) audit teams to enable more comprehensive audit testing and to increase the use of data analytics overall. Includes assisting CAS audit teams in understanding their data, offering innovative data analytics solutions, and providing technical assistance as required.
4.Interfacing with Technology Operations Services (TOS) regarding application system particulars.
5.Interfacing with the lines of business via walkthroughs and other interactions to gather information relevant to the audit test being performed.
6.Coaching less-experienced Data Analytics staff on CAATs and other projects.
7.Performing other duties as requested by CAS Management.
Bachelor's degree in a quantitative field such as econometrics, computer science, engineering or applied mathematics, or equivalent work experience
Five to seven years of statistics or analytics experience
1.Seven or moreyears of data analytics experience.
2.CIA, CISA, ACDA or other relevant professional designation or advanceddegree.
3.Relevant technical knowledge (software tools like SQL, SAS, ACL, VBA, Python,mainframe and distributed services programming, data mining, datavisualization).
4.Ability to independently translate complex business scenarios into efficientand effective data analytic solutions.