Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, metro location, and mid-level generalist analytics role increase applicant competition.
Role requires banking audit methodology and domain knowledge, limiting cross-industry transferability.
Explicit 6–8 year requirement plus mandatory SQL/Python/Spark and audit domain knowledge enforces strict filtering.
Lead end-to-end execution of audit analytics from data sourcing to insight delivery, supporting audit lifecycle phases including planning, fieldwork, and reporting.
Design and implement AI-driven, autonomous analytics pipelines to automate data gathering, anomaly detection, and audit workflows, improving audit coverage and efficiency.
Collaborate with global audit teams and technology stakeholders to identify and apply analytics and automation opportunities within Internal Audit across multiple banking domains.
6-8 years of experience as a business or audit analyst delivering analytics and automated solutions.
Master's degree in Computer Science, Information Technology, Mathematics, Statistics, Finance, or related quantitative field.
Proficiency in SQL, Python, Hadoop ecosystem (Hive, PySpark, Apache Spark), SAS, and data visualization tools such as Tableau, MicroStrategy, or Cognos.
Experience working in a global, large, complex organization and familiarity with AI tools, large language models, and audit analytics methodologies.
Strong technical background with hands-on programming and data engineering skills focused on audit analytics and automation in a regulated banking environment.
Experienced in applying AI/ML tools and frameworks for data extraction, anomaly detection, and workflow automation within Internal Audit or risk contexts.
Operates effectively across multicultural and matrix organizations, collaborating with audit, technology, and business teams on analytics strategy and delivery.