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Data Analyst Internship

At COUNTRY Financial we pride ourselves on offering a competitive and enriching internship program. As an intern you will be part of the COUNTRY family, be assigned real and meaningful work, partner with a mentor, attend speaker sessions with employees of all levels, learn about future career opportunities, participate in a case study competition, have ample opportunities to network within the organization, volunteer in our community, and so much more! We're excited you are considering us to enhance your college and internship experience.
 
Responsibilities:

  • Analysis and reporting of patterns, insights, and trends to decision makers.
  • Collect, aggregate, and analyze data from multiple internal and external sources to drive insights into business performance.
  • Produce actionable reports that show key performance indicators, identify areas of improvement into current operations, and display root cause analysis of problems. Use analytics and metrics to improve processes and provide data-driven forecasts of potential costs, risks, and profits of new business initiatives.
  • Communicate findings and insight to stakeholders and provide business strategy recommendations for optimizing business performance.
  • Provide reporting solutions and respond to ad-hoc report requests across multiple business area.
  • May participate in the design and development of business intelligence reporting tools and data structures.
 
Requirements:

  • Must be able to work full-time hours from late May to early August 2022.
  • The internship may be extended part-time into the fall semester; depending on the availability of the student, the needs of the company, and strong work performance.
  • Graduation date of December 2022 or beyond.
  • Pursuing a degree in Data science or Management and Qualitative Math.
  • Strong Data Visualization Skills.
  • Excellent problem-solving skills.
  • Ability to performs data collection and data analytics using basic Microsoft tools.
  • Basic understanding of statistics and data structure.