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Tier-1 brand, metro location, mid-level generalist data role with broad skills increases applicant competition.
Skills are transferable, but banking operations and regulatory experience increase domain-specific fit requirements.
Explicit 3+ years plus mandatory SQL/Python/Tableau/SAS/PySpark and banking domain requirements.
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Drive development and implementation of analytical solutions supporting Banking Operations & Analytics under COO.
Design, develop, automate, and maintain reports and dashboards using tools like Tableau, Python, SQL, SAS, PySpark.
Analyze workflows to improve efficiency via data and process optimization, including automation of manual tasks.
3+ years experience in Reporting, Automation, and Data/Information Management roles.
Proficiency in SQL, Python, SAS, PySpark, Tableau or equivalent BI/reporting tools.
Bachelor’s degree in STEM required; Master’s preferred.
Experience with banking operations analytics (e.g., expense analytics, fraud analytics) and knowledge of data privacy and security regulations.
Strong analytic and scripting skills with proven ability to deliver impactful data insights and automation solutions.
Experience working with large, complex datasets and developing scalable analytics frameworks in a banking or financial services environment.
Demonstrated ability to develop and deploy AI/Gen AI solutions in partnership with technology and business teams to influence key business drivers.