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Mid-level generalist data role in metros with common Python/SQL skills yields high applicant density.
Banking-specific collateral and regulatory experience moderately limits cross-industry applicability.
Explicit 3–6 years plus mandatory Python/SQL and banking domain knowledge creates strict screening.
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Conduct detailed gap analysis of trading data from multiple source systems and identify discrepancies.
Develop and maintain automated gap reporting and data extraction/transformation using Python and SQL.
Collaborate with stakeholders to understand system logic, present findings to senior management, and manage project documentation to PMO standards.
3-6 years experience with 3-5 years specifically in banking data analysis and problem solving.
Advanced proficiency in Python programming including pandas, strong SQL skills, and experience with data visualization tools like Power BI or Python libraries.
Location: Mumbai, Bangalore, or Pune.
Understanding of collateral management principles and regulatory requirements is beneficial but not strictly mandatory.
Experienced in banking domain data analysis with ability to handle complex data reconciliation and process improvement.
Proficient in Python and SQL for automation of data workflows and reporting in financial services projects.
Capable of managing stakeholder interactions and delivering actionable insights to senior management within a project management framework.