Data AI Co Op / Internship

BrainPOP•New York, NY

5d•Hybrid

About The Position

BrainPOP's Data team collaborates on enterprise analytics initiatives, providing the business with up-to-date data assets. They partner with various departments like Finance, GTM, and Product to understand challenges and deliver actionable, data-driven insights. Their work involves traditional analytics, designed experimentation, dashboard reporting, and AI-driven approaches such as creating semantic models for self-service insights, utilizing Cortex AI for predictive modeling (e.g., churn prediction), and developing Python applications for content analytics. This co-op/internship role focuses on empowering analytics with AI, offering a full-stack experience that covers analytics, experimentation, reporting, data modeling within analytics engineering, and a strong emphasis on AI capabilities. The ideal candidate is curious about leveraging cutting-edge technologies and AI to accelerate business impact. This position is well-suited for individuals who thrive in dynamic, agile environments and possess an experimental mindset, enabling them to collaborate effectively with the Data team and business stakeholders across Marketing, Product, Finance, and GTM. Interns will gain exposure to the systems, tools, and AI pipelines used for business optimization and have the opportunity to work on real-world business problems. The data stack includes modern tools such as Snowflake, dbt, Airflow, AWS, Streamlit, Python for experimentation, AI platforms like CortexAI and NotionAI, Tableau for BI, and Salesforce as the CRM.

Requirements

Pursuing a Bachelor’s degree (senior preferred) or a Master’s degree in Computer Science, Computer Engineering, Data Science; recent Bachelor’s/Masters graduates may be considered
Background in analytics, data, data engineering or a tech adjacent role
Full stack capability spanning analytics, data modeling, AI, and analytics engineering
Team player; able to work independently, as well as collaboratively within the Data team and cross functionally
SQL, including CTEs & window functions (Snowflake experience a plus)
Python — comfortable writing Python for data transformation and automation
AI-assisted development — Experience using an LLM coding assistant like Claude or equivalent to structure prompts clearly
Some experience in prompt engineering — Ability to write a structured prompt (YAML + Markdown or equivalent) that helps others think through context, instructions, examples, and output format
Some experience building dashboards or data visualizations that tell a clear business story with tools like Tableau

Nice To Haves

dbt — Model authoring & YAML tests in a cloud warehouse context
Snowflake Cortex — Cortex Analyst, Cortex Agents, Dynamic Tables, semantic views or ability to learn quickly
Comfortable working in Git (PRs, branches, code review)
Understands stakeholder needs and can translate between the worlds of AI, data, and business to enable strategic insights
Understands subscription based business models
Basic understanding of statistics/experimental design

Responsibilities

Enhance analytics, experimentation, and BI capability for business
Produce ad-hoc analysis from Snowflake or other in-house telemetry systems for Marketing, Product, Finance, and GTM
Perform data modeling & validation for Tableau dashboards, including deployment
Translate Tableau workflows into Streamlit apps for experimentation
Analyze teacher segmentation & usage patterns within products
Monitor key performance indicators (KPIs) related to user engagement, product usage, and revenue metrics, identifying areas for improvement and optimization
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 reusable, invokable tools using Snowflake and dbt, modeled in the semantic layer for quick business insights through CortexAI
Transform raw Snowflake data into reusable data models that can be pipelined into dbt & the semantic layer
Assist in modeling, documentation & QA for CortexAI models to support semantic view for natural language query capability
Write and iterate on prompt & skill structures (YAML + Markdown skill files) based on output quality and stakeholder feedback
Evaluate model outputs rigorously and enable business to produce analyst-quality output using semantic layer capability