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Tier-1 brand, mid-level generalist analytics title, metro location, and common toolset increase competition.
Strong credit-card banking domain knowledge requirement reduces cross-industry transferability.
Explicit 5–7 years, mandatory SAS/SQL/Python, and credit-domain expertise make filters stringent.
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Analyze operational credit card and consumer banking data using SAS, SQL, or Python to assess business performance and identify improvement areas.
Formulate and recommend data-driven strategic actions related to portfolio management, customer engagement, and profitability.
Communicate insights and collaborate with stakeholders and senior leadership to implement data-informed decision strategies while managing risk and compliance.
5-7 years of professional experience, preferably in the banking domain.
Hands-on experience with SAS, SQL, and/or Python for data analysis and manipulation.
Strong understanding of credit business including credit cards and personal loans, with knowledge of key performance drivers and risk principles.
Bachelor's degree or equivalent experience; Master's preferred in Statistics, Economics, Business Administration (MBA), or related field.
Experienced analyst with demonstrated ability to independently interpret complex banking and credit card sector data and derive actionable business insights.
Capable of managing stakeholder relationships and communicating effectively to senior leadership.
Organized, detail-oriented professional skilled in process management and integrating business knowledge with data analytics to influence decision-making.