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Mid-level data analytics role, metro location, broad skillset and popular profile increases applicant competition.
Core data analytics skills are broadly transferable across industries despite audit/financial services context.
Explicit 3–7 years requirement and mandatory SQL, analytics tools and audit experience raise screening rigor.
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Develop and maintain data analytics dashboards, scripts, and continuous monitoring solutions for Internal Audit.
Support AI and analytics initiatives within Internal Audit and maintain the Audit Universe tool.
Lead reporting, performance analysis, operational standards, and IA transformation initiatives, including managing IA data quality and stakeholder engagement.
3 to 7 years of hands-on experience mining and analyzing data using databases and analytic software in Financial Services, preferably insurance or investment management.
Strong knowledge of SQL in a relational database environment.
Experience or knowledge of internal audit or audit environments is ideal.
Degree and/or relevant professional qualification or relevant consulting/industry expertise.
Experienced in financial services internal audit with strong operational and data analytics understanding.
Proficient in scripting languages (Python, Visual Basic), data visualization tools (Power BI, Tableau), and predictive modeling/statistical software (R, SAS).
Able to manage multi-stakeholder reporting, drive audit operational improvements, and support IA transformation projects effectively.