Data Scientist

• 3 or more years of hands-on data science in fast-paced business environments, at Tier 1 consultancies, Big Tech, high-growth start-ups and scale-ups, or media industry leaders
• Python: expert-level proficiency with the standard data science and ML frameworks, and SQL as a daily tool
• Data acquisition: you have scraped and acquired raw data from new sources, building creative solutions to reach datasets beyond standard APIs
• Statistical rigour: you design and read experiments properly, you know when a signal is noise, and you have run A/B tests or causal analyses that changed a decision
• Models in production: you have deployed models that people actually used, and you know what it takes to keep them honest over time
• AI-native: extensive hands-on experience with agentic coding tools and LLMs in your data workflows
• From data to decision: you find the opportunity in the data and propose the next step, and your dashboards and visualizations (standard libraries or Tableau) are the ones leadership trusts
• Collaboration: you work well across engineering, product and business teams, and colleagues would describe you as hard-working, ambitious and persistent
• Pace: you thrive in a fast-paced and performance-oriented environment
• A big plus: you're obsessed with music, video or social media

We look for battle-tested data scientists who understand that real impact comes from turning messy, unstructured data into business-critical insights that drive company direction. You don't just build models: you solve business problems by finding creative ways to access hard-to-reach data and translating statistical findings into actions the team takes.

Typically, your profile will look like this:

• Background: a degree in Data Science, Statistics, Computer Science, Physics, Math or a related quantitative field