Finance/ Data Analytics Intern - Global Markets

Rich Products CorporationBuffalo, NY
Onsite

About The Position

Rich's, also known as Rich Products Corporation, is a family-owned food company dedicated to inspiring possibilities, with products ranging from cakes and icings to pizza, appetizers, and specialty toppings. They serve homes, restaurants, and bakeries globally, providing creative solutions to food industry professionals. With over 13,500 associates in 100 countries and annual sales of $5.8 billion, Rich's is a global leader. This internship offers an exciting opportunity for a student with a strong interest in data analytics and data science to apply analytical skills in a real-world corporate finance environment. The internship will be in-person at the World Headquarters office in Buffalo, NY, working approximately 25 hours/week, starting in early June.

Requirements

  • Must be enrolled in an accredited college or university, working towards earning a Bachelor's or Masters degree (concentration in Data Analytics, MIS, Computer Science, Finance, Accounting or related field)
  • Must have a 3.0 GPA or higher.
  • Proficiency with Microsoft Office suite (Excel, PowerPoint, Word) required
  • Functional competencies to include strong financial & interpersonal/communication skills.

Nice To Haves

  • Familiarity with Business Intelligence (BI) dashboard and visualization tools preferred

Responsibilities

  • Analyze large financial and operational datasets using Excel, Power BI, or other reporting tools
  • Develop data models, dashboards, and visualizations to support trend analysis and performance tracking
  • Perform data validation and reconciliation to ensure accuracy in financial reporting.
  • Utilize data analytics to identify financial trends, opportunities, and risks, and develop strategies to optimize financial performance.
  • Extract and prepare data for analytic projects.
  • Provide decision support by turning financial data into business insights when evaluating current performance, future forecast, and new business opportunities.
  • Support additional projects to find correlations across financial data captured with other data sets
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