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Strong brand, mid-level generalist data role with broad toolset and metro appeal increases applicant competition.
Core analytics skills are transferable but pricing and revenue-management experience favors industry-specific candidates.
Explicit five-year senior requirement plus technical analytics and pricing expertise increases selection rigidity.
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Lead and execute advanced data analysis and predictive modeling projects to deliver actionable business insights and support senior leadership decision-making.
Manage multiple complex analytical assignments concurrently, including exploration of diverse data sources and identification of trends, patterns, and anomalies.
Present findings and strategic recommendations effectively to senior executives, driving stakeholder understanding and business impact.
5 years of relevant data analysis experience (Senior II level).
Bachelor’s degree in Computer Science, MIS, Mathematics, Statistics, or similar quantitative discipline; Master’s or PhD preferred.
Proficiency in data analytics tools such as Oracle, SQL Server, Teradata, SAS, Python, and visualization tools like Tableau, PowerBI, or Spotfire.
Experience with data and business analytics, advanced statistics, predictive modeling, and stakeholder/project management.
Demonstrated ability to lead cross-functional analytics projects from concept to execution with minimal supervision.
Experience with pricing and revenue management analytics (yield management, customer segmentation, revenue impact) is a plus.
Comfortable working with both structured and unstructured data from multiple disparate sources and communicating complex data findings to diverse leadership audiences.