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Data Science Intern
The J.M. Smucker Co.. Collect, clean, and analyze large datasets from multiple sources using statistical and programming techniques .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in statistical modeling, machine learning, and data analysis, with proficiency in programming languages such as Python, R, or SQL. Capable of effectively communicating complex data insights through visualizations and presentations while collaborating with cross-functional teams to drive business outcomes.
Highest-signal resume keywords
Statistical ModelingMachine LearningData AnalysisData VisualizationProgramming (Python, R, SQL)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical ModelingMachine LearningData AnalysisData WranglingForecasting
Soft Skills
Problem-SolvingCommunication
Tools & Technologies
TableauPower BIMatplotlibGgplot
Industry Keywords
Data ScienceQuantitative AnalysisCross-Functional CollaborationBusiness Insights
Tech Stack
Tools & technologiesPythonSQLTableau
About the role
Key responsibilities & impact- 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
What you’ll need- 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
Comp & perks- 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