Data AI CO OP Internship positions focus on delivering results in their domain. This page aggregates open Data AI CO OP Internship roles and what employers typically expect.
For over two decades, BrainPOP has been trusted by educators and parents worldwide as a source of engaging and impactful learning experiences for all kids. With a presence in over two-thirds of U.S. districts through school and district subscriptions and an estimated annual reach of 25 million students, BrainPOP is empowering kids to take agency over their learning and excel in and out of the classroom. The company was acquired in 2022 by KIRKBI, the family-owned holding and investment company of the LEGO brand, marking a significant milestone as their first acquisition in the digital learning realm. We are thrilled to continue making learning fun and accessible with the strategic guidance and support of KIRKBI. ## **About the Role** BrainPOP’s Data team works across enterprise analytics initiatives to empower the business every day with the latest and greatest data assets. We partner with Finance, GTM, Product and all other parts of business to understand their challenges and provide them with actionable data-driven insights. We pair traditional analytics, designed experimentation and dashboard reporting with AI-driven approaches, like creating semantic models to help business self-serve with real-time insights, Cortex AI-based data science models to predict churn, and python applications to drive movie content analytics. In this co-op/internship, you’ll learn about empowering analytics with AI - a full stack experience that will span across analytics, experimentation, reporting, data modeling within analytics-engineering along with strong focus on AI based capabilities. We are looking for someone who has the curiosity to use the latest and greatest technologies plus AI as an impact-accelerator across the enterprise. This role is a great fit for someone who thrives in a dynamic and agile environment and can move with an experimental mindset to work with the Data team & business stakeholders in Marketing, Product, Finance and GTM. You will get exposure to the systems, tools and AI pipelines we use to optimize our business along with the opportunity to work with real world business problems. Our data stack consists of modern data tools like Snowflake, dbt, Airflow, AWS along with Streamlit, python that we use for experimentations, AI platforms like CortexAI, NotionAI, Tableau on the BI side, Salesforce as our CRM. **Details** The opportunity will be from September (7 or 14) through December 18, 2026, Monday to Friday from 9:00 am to 5:30 pm Eastern (40 hours weekly, 8 hours daily with 30 minutes lunch). We are a hybrid workplace, and a candidate within commutable distance of our NYC office (Flatiron area) who is available to spend Wednesdays in the office is strongly preferred. The pay rate is $25/hour. Please note: BrainPOP does not offer relocation, housing or travel assistance. ## In This Role, You Will *Enhance analytics, experimentation and BI capability for business* - Produce ad-hoc analysis from Snowflake (our Data Warehouse) or other in-house telemetry systems as required for Marketing, Product, Finance and GTM with focus on - Data modeling & validation as required for Tableau dashboards, along with deployment of dashboards as needed - Translating Tableau workflows into Streamlit apps as required for experimentation - Analysis of teacher segmentation & usage patterns within our products - Monitor key performance indicators (KPIs) related to user engagement, product usage, and revenue metrics. Identify areas for improvement and optimization and provide recommendations to enhance performance & identify trends, patterns and opportunities - Ensure data accuracy, consistency, and completeness across all systems *Support building AI workflows within the CortexAI semantic layer* - Design data models and analytic frameworks for repeatable workflows- product usage analytics, account churn, book of business renewals, customer feedback - and turn them into a reusable, invokable tool using Snowflake and dbt, modeled in the semant…