Thndr
Investment
Data&ContentIntelligenceIntern
Neural analysis suggests this role is
optimal for Entry candidates.
“Data & Content Intelligence Intern at Thndr. Skills: Data analysis, SQL, Python, Machine Learning/NLP, Insight Generation. Collect, clean, and analyze data from Superset, Intercom, Braze, Google Sheets, internal tools, and other data sources to uncover user behavior, content gaps, and recurring questions.. Write SQL queries, work with dashboards, and build structured trackers that help the content team understand what users are asking, where they are getting stuck, and which topics need better c”
What You'll Achieve.
help us create smarter, more useful, more data-driven content based on real user behavior; turn user data into better content decisions
Industry & Context.
analytical thinking and the ability to turn data into clear insights, not just numbers
What They're Looking For.
Must Have
Senior year student or recent graduate in Data Science, Computer Science, Engineering, Business Analytics, Economics, Statistics, or a related field, Google Sheets or Excel skills, including formulas, lookups, pivot tables, cleaning, and structured reporting, Good SQL skills and comfort extracting data from databases or dashboards, Basic Python scripting ability for cleaning, automation, data analysis, and working with files or APIs, Ability to work with APIs and technical documentation, Comfort working with messy, incomplete, or unstructured datasets, analytical thinking and the ability to turn data into clear insights, not just numbers, Curiosity about user behavior, content, product journeys, and how people search, ask, misunderstand, or get stuck, Ability to communicate findings clearly to non-technical teams
Nice to Have
Experience with Superset, Intercom, Braze, CRM data, customer support data, product analytics, or content performance analysis, Familiarity with basic machine learning or NLP concepts such as clustering, classification, tagging, or text analysis
What You'll Do.
and analyze data from Superset
and other data sources to uncover user behavior
and recurring questions.
and build structured trackers that help the content team understand what users are asking
where they are getting stuck
and which topics need better content.
Use Python to clean messy datasets
automate repetitive tasks
and prepare data for deeper analysis.
Make API calls to pull data from different platforms and support lightweight workflows that keep content insights updated.
Use basic ML or NLP techniques to cluster and classify user questions
support conversations
and content gaps by theme
Work with the Data Engineering team to define
and refresh the data sources needed for recurring content intelligence reports.
Turn raw data into clear recommendations that help us decide what content to create
Document your analysis
and recurring reports so the team can reuse and build on your work.
How You'll Work.
Team & Collaboration
Work closely with Content, CX, Growth, Product, and Data teams to connect user insight with better education, support, and communication.; Work with the Data Engineering team to define, connect, and refresh the data sources needed for recurring content intelligence reports.
Communication Scope
Ability to communicate findings clearly to non-technical teams
Full Job Description
ABOUT THE ROLE We are looking for a Data & Content Intelligence Intern to help us turn user data into better content decisions. This role sits at the intersection of data analysis, automation, user insight, and content strategy. You will work with data from tools like Superset, Intercom, Braze, Google Sheets, APIs, and internal systems to help us understand what users are asking, where they are getting stuck, what they misunderstand, and which content gaps we need to solve next. You will use tools like SQL, Python, Sheets, APIs, and basic ML/NLP techniques to clean, analyze, classify, and structure data into insights the content team can actually act on. The goal is simple: help us create smarter, more useful, more data-driven content based on real user behavior. WHAT YOU'LL DO - Data Analysis: Collect, clean, and analyze data from Superset, Intercom, Braze, Google Sheets, internal tools, and other data sources to uncover user behavior, content gaps, and recurring questions. - SQL & Reporting: Write SQL queries, work with dashboards, and build structured trackers that help the content team understand what users are asking, where they are getting stuck, and which topics need better content. - Python & Automation: Use Python to clean messy datasets, merge data, automate repetitive tasks, write scripts, and prepare data for deeper analysis. - API Integration: Make API calls to pull data from different platforms and support lightweight workflows that keep content insights updated. - Machine Learning & Classification: Use basic ML or NLP techniques to cluster and classify user questions, support conversations, search queries, and content gaps by theme, intent, product, or journey stage. - Data Workflows: Work with the Data Engineering team to define, connect, and refresh the data sources needed for recurring content intelligence reports. - Insight Generation: Turn raw data into clear recommendations that help us decide what content to create, rewrite, prioritize, or test
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