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Tier-1 bank, Bangalore, mid-level analytics role with broad skillset increases candidate competition.
Strong banking audit domain and controls knowledge required, reducing cross-industry transferability.
Explicit 6-8 years, mandatory SQL/Python/Hadoop and domain knowledge enforce strict technical shortlisting.
Lead design and execution of advanced audit analytics and automation across the audit lifecycle to enhance audit coverage and operational efficiency.
Develop and implement AI-driven solutions including large language models and autonomous analytics pipelines to reduce manual effort in audit processes.
Collaborate globally with audit, technology, and business teams to identify analytics opportunities and deliver actionable insights supporting internal audit functions.
6-8 years experience as a business or audit analyst delivering analytics and automation solutions.
Master's degree in Computer Science, Information Technology, Mathematics, Statistics, Finance, or related quantitative field.
Proficiency in SQL (complex queries and performance tuning), Python (data wrangling, automation scripting), and experience with big data tools like Hive, PySpark, Apache Spark.
Experience applying AI tools, large language models, and AI orchestration frameworks to audit analytics; working knowledge of audit and risk frameworks in banking.
Experienced in global, complex organizations with exposure to banking domain audit processes, risk frameworks, and controls.
Strong technical skillset combining data engineering, AI-driven analytics, and audit methodology implementation.
Capable of independently managing end-to-end analytics projects and collaborating across multicultural and multidisciplinary teams in a professional environment.