CenterWell | Senior Data Analyst – Pharmacy Pricing Strategies | Louisville, KY | United States | BigDataKB.com | 2022/10/30

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Job Location: Louisville, KY

The Senior Data Analyst coordinates with other analytics, IT and business areas across the organization to ensure work is completed with insights from knowledge SMEs. The Senior Data Analyst work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors.


Responsibilities

The Senior Data Analyst leverages its advanced knowledge of data, modeling, optimization, and tools. Applies disciplined analytics to predict behavior and optimize programs and products to maximize revenue growth. Contributes to more innovative approaches to financial models as it builds knowledge of the business context in which it operates. Understands and analyzes complex data, articulates to various units within the company at the appropriate level, impacts the business from mathematical concepts which have a potentially sizeable dollar impact on the business. Begins to influence department’s strategy. Makes decisions on moderately complex to complex issues regarding technical approach for project components, and work is performed without direction. Exercises considerable latitude in determining objectives and approaches to assignments.

Required Qualifications

  • Bachelor’s degree and 5 or more years of data analytics experience OR Master’s degree and 3 years of experience
  • Experience with coding languages and using data to drive business outcomes and decisions
  • Excellent verbal and written communication
  • Able to articulate and present findings and insights to senior leadership
  • Strong attention to detail
  • Must be passionate about contributing to an organization focused on continuously improving consumer experiences
  • 5 or more years of Excel experience


Preferred Qualifications

  • Advanced Degree
  • Pharmacy pricing acumen
  • Expertise in data mining, forecasting, simulation, and/or predictive modeling
  • Preferred technologies such as SAS, SQL, Power BI or similar tools

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Scheduled Weekly Hours

40

Not Specified

0




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