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Tier-1 brand, metro location, mid-level generalist analytics role increase applicant competition.
Core data analytics skills transfer across industries, but banking campaign domain knowledge moderately matters.
Explicit years and mastery of Python and Hive/SQL make screening moderately strict.
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Lead analytics initiatives to enhance Retail Bank business productivity and build customized solutions across customer lifecycle, branch/network, small business/mortgage, and digital engagement analytics.
Analyze campaign performance, conduct market trend analysis, and provide actionable recommendations to improve customer acquisition, retention, and campaign profitability.
Collaborate with Marketing, Pricing, and Decision Management teams to influence revenue growth and ensure compliance with security and performance standards.
2 years of experience with a Master's degree or 4 years with a Bachelor's degree in Computer Science or a related quantitative field.
Proficiency in Python and Hive/SQL required.
Experience in marketing research, statistical or data analysis preferred but not mandatory.
Work Experience Required: 2 years with Master’s or 4 years with Bachelor’s degree.
Able to translate complex data analyses into actionable business insights to optimize customer lifecycle and campaign strategies.
Experienced in working cross-functionally with business leadership and marketing teams to drive data-driven decision making.
Comfortable handling large datasets and statistical analysis using Python and Hive/SQL in a Retail Banking context.