CHS has an exciting opportunity in our Global Grain & Processing group. We are looking for a Data Analytics Intern to help support a variety projects that will range in scale and complexity. You’ll have the opportunity to develop your skills by learning from and collaborating with a talented team of business and IT professionals.
As a Data Analytics Intern, your assignments may include, but are not limited to:
- Work closely with data scientists and analysts to design and develop data cubes in our Power BI business information tools to report key business information.
- Participate in engagement and discovery sessions between data scientists and data analyst to identify problems/gaps as well as innovation opportunities that can be solved with data analytics.
- Participate in the design of dashboards for business intelligence.
- Research and test solutions in a POC (proof of concept) scale to operationalize the outcomes and validate the results in the real-world.
- Become a part of a successful, dynamic team using standard Lean & Agile processes to deliver quality and timely results to internal customers.
- Be encouraged and expected to innovate and be creative in your data analysis, problem solving and presentation of solutions.
- Potential for RPA work.
Minimum Qualifications (required)
- Currently enrolled in in Business Analytics, Mathematics, Economics, Physics, Computer Science, Engineering, or similar degree program at an accredited institution, entering junior or senior year, or recent graduate.
- 0-1+ years of experience with the following:
- Data visualization tools – e.g. Power BI or Office 365
- Working knowledge or experience with SQL
- Excellent communication skills, customer focus, strong analytical and problem-solving skills, self-motivated with confirmed leadership abilities, presentation skills and be able to function in a team-oriented environment with resource and time constraints.
- A passion for customers, engineering and product quality
- Training/Experience with the following:
- Database management technologies in the data analytics context
- Data analytics/science areas, such as time series analysis, forecasting, classification and regression analysis
- LEAN and/or Agile concepts/methodologies