Data Scientist - E-commerce

About the position

Position Summary, Responsibilities and Expectations: Perform customer, product, and behavioral segmentation analysis using transactional, browsing, and content data Analyze e-commerce performance metrics and experiment results to identify trends, opportunities, and optimization levers Support AI-driven use cases such as personalization, merchandising intelligence, and content optimization Design and analyze A/B tests to evaluate changes in content, merchandising, or customer experience Work with e-commerce and content platforms such as Contentful , Jasper , and Omnify to understand data structures, workflows, and optimization opportunities Support MCP-aware workflows where analytics, models, or tools exchange contextual data across systems Assist in building and maintaining data analysis pipelines and exploratory models using Python Collaborate with cross-functional teams across E-Commerce, Data Science, Marketing, and Engineering Document analyses, experiments, assumptions, and insights clearly for internal stakeholders

Responsibilities

• Perform customer, product, and behavioral segmentation analysis using transactional, browsing, and content data
• Analyze e-commerce performance metrics and experiment results to identify trends, opportunities, and optimization levers
• Support AI-driven use cases such as personalization, merchandising intelligence, and content optimization
• Design and analyze A/B tests to evaluate changes in content, merchandising, or customer experience
• Work with e-commerce and content platforms such as Contentful , Jasper , and Omnify to understand data structures, workflows, and optimization opportunities
• Support MCP-aware workflows where analytics, models, or tools exchange contextual data across systems
• Assist in building and maintaining data analysis pipelines and exploratory models using Python
• Collaborate with cross-functional teams across E-Commerce, Data Science, Marketing, and Engineering
• Document analyses, experiments, assumptions, and insights clearly for internal stakeholders

Requirements

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, Economics, Business Analytics, or a related field
• Strong proficiency in Python for data analysis
• Solid understanding of statistics, experimentation, and basic machine learning concepts
• Experience working with structured datasets using tools such as Pandas and NumPy
• Strong analytical and problem-solving skills
• Ability to communicate findings clearly to both technical and non-technical audiences
• Prior exposure to e-commerce, digital retail, or online marketplaces
• Experience with customer segmentation, cohort analysis, and A/B testing methodologies
• Familiarity with AI or ML frameworks such as scikit-learn, PyTorch, or TensorFlow
• Exposure to content management or AI content tools (e.g., Contentful, Jasper, Omnify)
• Exposure to Model Context Protocols (MCP) or context-aware, agent-based workflows
• Understanding of experimentation platforms or conversion optimization frameworks
• Exposure to modern data stacks or cloud environments is a plus
• You are actively enrolled as a full-time student in an accredited institution and have completed at least one year of education.
• Able to work 40 hours a week onsite throughout the course of the 12-week summer internship either between (May 27 – August 13 th , 2026 OR June 16 th – September 13 th , 2026)
• Legally authorized to work in the United States

Nice-to-haves

• Exposure to modern data stacks or cloud environments is a plus

Benefits

• This internship includes a base pay rate of \$30 per hour and holiday pay.