Fall Data Intern

Vendelux is building the category-defining platform for event marketing intelligence.

Events are one of the largest and most impactful marketing channels, yet historically one of the least measurable. Vendelux brings transparency and performance to this space — helping companies discover, evaluate, and optimize their event strategy with data.

Our platform powers thousands of event decisions by delivering proprietary, AI-driven insights across hundreds of thousands of events globally. At the core of our platform is a robust ecosystem of event organizer partnerships — where organizers share first-party data, enabling richer insights for customers while receiving benchmarking and audience intelligence in return. From identifying the highest ROI conferences to enabling targeted meeting programs, Vendelux helps companies turn events into a predictable and scalable growth engine.

In addition, Vendelux Meetings extends our platform by turning insights into pipeline — using AI to identify high-value attendees and proactively book 1:1 meetings between our customers and their ideal prospects at events. This enables go-to-market teams to drive measurable ROI and maximize every event interaction.

Founded in 2021, Vendelux is a Series B SaaS company backed by top-tier investors including FirstMark. We partner with many of the fastest-growing companies in the world, and our team includes leaders from Bain, ZoomInfo, Shutterstock, FanDuel, Compass, Airbnb, Forter and beyond.

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We're looking for a technically-minded person eager to work on real data problems at a fast-growing startup. This is a paid, onsite role for a local college or MBA student who can commit ~20+ hours/week. You'll work directly on the data team — writing SQL, building pipelines, and using AI tools to power the insights our platform depends on. For the right person, this could develop into a full-time role.

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  Write SQL queries to analyze events, attendees, and organizations; surface insights that directly inform product and business decisions

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  Build and maintain dashboards to monitor data quality and pipeline health

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  Identify and resolve data errors in our database; investigate patterns and potential root causes

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  Use and evaluate AI/LLM-enabled tools to generate, validate, and manage large datasets

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  Conduct structured research to identify and validate key data inputs for machine learning models

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  Collaborate with the data and engineering teams on data infrastructure and tooling improvements

• Based in New York City and able to work from our Midtown office

• Available ~20+ hours per week

• Proficiency in SQL — you're comfortable writing non-trivial queries against real datasets

• Familiarity with Python is a strong plus

• Experience with dashboarding tools (Looker, Metabase, Tableau, or similar) is a plus

• Detail-oriented with high ownership over your work

• Genuinely curious about data, AI, and how systems are built