Applied AI & Data Intern / Co-op

As an Applied AI & Data Intern, you will support the development of data processes, reporting tools, and analytics solutions that empower Product and Sales teams to make informed, data-driven decisions.

A significant part of the role involves contributing to Agentic AI initiatives, where you will help design, test, and refine AI agents that automate workflows, enhance decision-making, and improve operational efficiency. This internship provides a unique opportunity to work hands-on with emerging AI technologies and apply them to meaningful, real-world business problems.

This position is ideal for a student who is curious, analytical, and eager to build practical skills in modern data systems, applied AI, and automation.

What You Will Be Doing

• Contribute to Agentic AI initiatives, including:

• Assisting in the design, evaluation, and refinement of AI agents

• Testing and validating agent behaviors, prompts, workflows, and tool integrations

• Preparing, curating, and structuring data used to train and improve AI agent performance

• Collecting feedback from internal users to enhance agent reliability, alignment, and usability

• Develop and maintain data solutions by building and improving data pipelines, dashboards, and reports using SQL, Python, BI tools (Power BI, Tableau, etc.), and agentic AI-driven automation.

• Support data quality efforts through cleaning, validating, and organizing datasets sourced from multiple systems and platforms.

• Document data processes – including workflows, business logic, and reporting definitions to ensure consistency, transparency, and reusability across the team.

• Contribute to analytics projects across areas such as product, sales, pricing, and risk by preparing datasets, conducting exploratory analysis, and summarizing key insights.

• Assist in the development of KPIs, metrics, and visualizations that support stakeholder decision-making and operational visibility.

• Participate in broader AI and automation initiatives, including prototype testing, requirement gathering, and preparing training or evaluation data used in AI-driven tools.

• Collaborate with cross-functional teams, including product, analytics, data, and operations, on day-to-day tasks, project execution, and continuous improvement activities.