Data Science Internship

Our Mission:

As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing.

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We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more.

Where you’ll work:

This is a hybrid role and requires in-office collaboration in Ghent three times per week.

The Team or Role:

As a Data Scientist Intern on Tinder’s Modes team in Ghent, you’ll help build new ways for people to meet on Tinder, from group and shared experiences to new modes of using the app. You’ll work with product, engineering, and data science partners to understand how members use these experiences, define how we measure success, and turn insights into product decisions.

In this role, you will:

• Design and execute A/B experiments to measure the impact of product features and algorithmic changes.
• Help build and improve the team’s experimentation and analytics tooling, including AI-assisted workflows, with a focus on standardization, automation, and clear documentation.
• Take a scoped analysis from question to recommendation, with guidance from your mentor.
• Collaborate with cross-functional partners in Data Science, Product, and Engineering to translate insights into actionable strategies.
• Present key findings and project outcomes to Product and Leadership teams during end-of-internship demos.
• Translate data insights into clear narratives and recommendations that inform product roadmaps and user experience improvements.
• Explore and analyze large-scale datasets to identify patterns, trends, and opportunities.

You’ll Need:

• Passion for using data and experimentation to solve complex problems.
• Intermediate to advanced SQL skills for data querying and analysis.
• Familiarity with / building to proficiency in Python.
• Strong foundation in statistics, probability, and experimental design (A/B testing, hypothesis testing).
• Clear written communication and a curious, fast-learning mindset.
• Comfort using AI tools (e.g., LLM-based coding and analysis assistants) as a regular part of your workflow, and the judgment to check their output.
• Currently pursuing a BS/BA, MS, or PhD in Computer Science, Data Science, Economics, Statistics, Applied Math, or a related field.