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Strong employer brand, metro location, common data-analyst title, and mid-level generalist requirements increase competition.
Core analytics skills transferable, but retail finance domain knowledge requirement increases industry specificity.
Explicit degree/experience bands and mandatory SQL/SAS/Python skills create strict shortlisting filters.
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Transform and visualize large datasets to meet project requirements supporting business growth and profitability.
Create and track key business metrics using data and analytical tools aligned with strategic objectives.
Ensure timely, accurate delivery of analytics with proper documentation following audit procedures.
Bachelor's or Master's degree in Statistics, Economics, Mathematics, or related quantitative fields (distance learning not accepted) OR 2 to 4 years of relevant experience without degree.
0 to 2 years of hands-on analytics experience if degree holder; otherwise 2 to 4 years of experience.
Knowledge of SQL, SAS, Python, or similar tools for data manipulation and analytics.
Work hours require availability between 06:00 AM to 11:30 AM Eastern Time for coordination with US and Asia teams.
Experience working with retail finance metrics or core concepts relevant to consumer and commercial analytics.
Ability to translate analytical results into actionable business insights and recommendations.
Comfortable working in a flexible, cross-functional team environment using tools like SAS, R, Python, and SQL.