The J.M. Smucker Co. · 23 hours ago

Data Science Intern (Masters or PhD), Summer 2025

United States

Internship

Remote

Intern

Start in 2025 Summer

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Responsibilities

Collect, clean, and analyze large datasets from multiple sources using statistical and programming techniques.

Interpret complex data to generate actionable insights and effectively communicate findings through dashboards, visualizations, and presentations.

Apply statistical modeling and machine learning techniques (both supervised and unsupervised) to solve real-world business problems in the sales domain.

Collaborate with cross-functional teams to support issue resolution, identify proactive improvement opportunities, and contribute to business outcomes.

Enhance your technical, analytical, and professional skills while building meaningful relationships across the organization.

Qualification

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Statistical ModelingMachine LearningData AnalysisPythonRSQLData VisualizationTime Series AnalysisForecasting

Required

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 (e.g., regression, classification, clustering), forecasting, and data analysis.

Proficiency in at least one programming language used in data science (e.g., Python, R, SQL).

Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib, ggplot) and an ability to tell compelling stories with data.

Relevant coursework completed, including but not limited to: Statistical Methods (e.g., Applied Statistics, Regression Analysis, Bayesian Statistics), Machine Learning (e.g., Supervised and Unsupervised Learning, Neural Networks, Deep Learning), Programming and Data Wrangling (e.g., Python for Data Science, Data Manipulation with R, SQL for Data Analysis), Data Visualization and Communication (e.g., Data Storytelling, Advanced Visualization Techniques), Domain-Specific or Advanced Topics (e.g., Time Series Analysis, Forecasting, Optimization Techniques, Econometrics).

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.