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Metro location, common data analyst title, broad SQL/SAS/Python skillset, and known employer increase candidate competition.
Core analytics skills transfer across industries, but retail finance domain knowledge moderately favors finance-experienced candidates.
Explicit degree requirements, precise 0-2 or 2-4 year bands, and mandatory SQL/SAS/Python skills raise shortlisting rigidity.
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Own extraction, transformation, validation, and visualization of large datasets to support business project delivery.
Create and track business metrics using analytical tools aligned with strategic objectives.
Ensure timely, accurate delivery and documentation according to audit standards.
Bachelor's or Master's degree in Statistics, Economics, Mathematics, or related quantitative field; distance learning degrees not accepted.
0 to 2 years of hands-on analytics experience or 2 to 4 years of experience without the degree.
Basic working knowledge of SQL, SAS, or Python for data manipulation and query execution.
Availability between 06:00 AM and 11:30 AM Eastern Time for collaboration with US and Asia teams.
Experienced in end-to-end data analytics including ETL processes and metric tracking in retail finance context.
Able to work with cross-functional teams leveraging tools like SAS, R, Python to deliver data-driven insights.
Comfortable working within US Eastern Time schedule for global coordination and flexible otherwise.