Data Analyst - Applied AI Intern, Buyer & Marketing Business Intelligence

About the Team

This position is part of the Data Analyst team within the Buyer & Marketing Product Line. Collaborating closely with analysts responsible for business metrics and stakeholder engagement, the team exploits data and AI technologies to enhance analytical efficiency and facilitate broad-scale business decisions. Responsibilities include developing reusable analytical solutions, automating routine workflows, and enabling consistent insights across multiple regions. The role combines data analysis, business decision support, and Applied AI, focusing on enabling analysts and business units to automate and scale analytical processes using AI-powered automation, reusable data agents, Text-to-SQL interfaces, and internal productivity tools. Interns will have access to advanced AI development resources, including dedicated credits for the Claude platform.

Job Description

• Collaborate with product managers and business stakeholders to grasp business goals, metric definitions, analytical needs, and decision-making frameworks.
• Spot repeated analytical tasks or business workflows which can be standardized or automated via AI-driven solutions.
• Convert business insights—defining metrics, understanding table relationships, calculations, and filters—into reusable agent capabilities, structured runbooks, and automated processes.
• Support monitoring of metrics and anomaly detection by linking business risk indicators with agent validation logic.
• Develop and refine LLM-powered analytics workflows for applications like Text-to-SQL, A/B testing analyses, and analytics covering multiple regions.
• Work together with regional stakeholders to comprehend market-specific business logic, reporting needs, and metric definitions.
• Utilize SQL, Python, Claude Code, and related AI tools to create internal tools, skill generators, SQL validators, and assessment utilities.
• Create test cases and validation frameworks aimed at verifying agent accuracy, consistency, and error management.
• Diagnose failure modes such as schema linking problems, omitted filters, incorrect computations, missing data, and improperly structured outputs, improving validation methods accordingly.
• Analyze execution logs and traces to enhance observability, maintainability, and the reliability of systems.
• Document best practices, workflows, and user manuals to facilitate adoption across teams and international markets.

Candidate Requirements

• Currently enrolled as a final-year or penultimate-year undergraduate or graduate student in fields like Business Analytics, Data Science, Computer Science, Information Systems, Statistics, Mathematics, Engineering, or related quantitative disciplines.
• Proficient in SQL, including advanced operations such as joins, aggregations, common table expressions (CTEs), window functions, and familiarity with data warehousing concepts.
• Experience in Python scripting for automation and data manipulation.
• Basic knowledge of A/B testing methodologies, experimental design, and interpreting statistical significance.
• Curiosity about how e-commerce metrics relate to business decisions and eagerness to learn domain-specific analytical workflows.
• Strong enthusiasm for large language model (LLM) applications, AI agents, workflow automation, and productivity tools for developers.
• Ability to translate business problems into analytical questions and devise effective solutions.
• Comfortable collaborating with cross-functional teams, including analysts, product managers, engineers, and business stakeholders.
• Excellent analytical thinking, problem-solving, communication, and documentation skills.
• Familiarity and comfort with AI coding platforms like Claude Code for reviewing, validating, and managing generated content.