Python Developer - Basketball Analysis (Internship)

SkillCorner provides physical and tactical performance data for professional sports teams and leagues.

The US Sports team builds the analytics products that turn our tracking data into insights for basketball (and, increasingly, American football) clients.

You will be mentored closely by two engineers on the US Sports team and work directly on products used by professional clubs and leagues.

This is afully remote position, open only to candidates based within Europe, in time zones within +/-2 hours of Central European Time (CET)

Responsibilities

• Build and ship features for our basketball analytics webapp.

• Help triage and fix bugs reported by client teams.

• Manage client requests, data access and day-to-day operational needs.

• Analyze platform users' behavior to optimize the previously mentioned features.
  
  

Must have

• Solid Python and SQL.

• Experience with Streamlit (personal or academic projects count).

• Ability to use AI coding agents in your workflow.

• Familiarity with a cloud environment (GCP or AWS).

• Experience with basketball-related projects (personal, academic, or professional)

• Professional working English.
  
  

Candidates for this internship must be able to provide avalid internship agreement(convention de stage)with their school or university, as this is a paid internship.

Nice to have

• French.

• Personal Streamlit or side projects, including well-executed vibe-coded ones (a big plus).

• Curiosity about sports analytics and eagerness to learn.

• Knowledge of American football.
  
  

Why join us?

• Your work powers decisions made by top professional clubs and leagues.

• Real ownership from day one: you ship features that clients actually use.

• Close mentorship from two engineers, with room to grow into cloud, data and multi-sport product work.

• A fast-moving, multi-sport environment (basketball and US football) with genuine technical challenges.
  
  

1. Phone screening: 20/30 min.

2. Technical test (take-home assignment, ~1 hour)