Data Science Intern

Posted 1hrs ago

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Job Description

Data Science Intern applying statistical modeling and machine learning to sales analytics at J.M. Smucker Company. Building dashboards and insights for business decision-making.

Responsibilities:

  • Collect, clean, and analyze large datasets from multiple sources using statistical and programming techniques
  • Interpret complex data to generate actionable insights
  • Communicate findings through dashboards, visualizations, and presentations
  • Apply supervised and unsupervised statistical modeling and machine learning techniques to solve real-world sales-domain business problems
  • Collaborate with cross-functional teams to support issue resolution
  • Identify proactive improvement opportunities and contribute to business outcomes
  • Enhance technical, analytical, and professional skills while building relationships across the organization

Requirements:

  • Enrolled in a graduate program (MS, PhD) in Statistics, Applied Mathematics, Data Science, Computer Science, Economics, Engineering, or a related quantitative field
  • Strong foundational knowledge in statistical modeling, machine learning, forecasting, and data analysis
  • Proficiency in at least one programming language used in data science, such as Python, R, or SQL
  • Familiarity with data visualization tools such as Tableau, Power BI, matplotlib, or ggplot
  • Relevant coursework in statistical methods, machine learning, programming and data wrangling, data visualization and communication, and domain-specific or advanced topics
  • Strong problem-solving skills with the ability to “connect-the-dots” across data and business needs
  • Good communication skills for presenting technical concepts to non-technical stakeholders

Benefits:

  • Unique opportunities to network and interact with company leadership
  • Customized professional development sessions
  • Competitive compensation package
  • Paid corporate holidays
  • Dedicated mentor
  • Hands-on training
  • Collaborative and supportive environment
  • Opportunities to connect with peers and leaders throughout the company