Senior Data Scientist

is building the operating system for the billion-dollar creator economy. Creators are held back by fragmented distribution, rented audiences, and technology that wasn't built for them.  is the unlock — the end-to-end Operating System designed to empower, grow, and scale what is irreplaceably human.

We work across four interconnected pillars:
Creator Media (reach, influence, trust), Creator Community (turning audiences into connected tribes), Creator Ventures (infrastructure for creators to build and back aligned businesses), and Creator Technology & Data Intelligence - the proprietary data suite that fuels the entire flywheel.

Powering all of it is our Innovation and Technology Organisation (ITO) - Steven's founding technical engine, operating in stealth mode to build the data and AI infrastructure underpinning our next stage of growth. Data Intelligence sits at the core of our long-term competitive moat.

We're looking for a builder to sit at the intersection of proprietary data, applied machine learning, and creative/social intelligence - building models and systems that turn one of the most unique datasets in the creator economy into insight and competitive advantage. This is hands-on and high-ownership: you'll work closely with engineering and product to translate data into decision-making tools, intelligence products, and AI-powered capabilities.

• Design, build, and deploy ML models and AI systems powering creator intelligence, audience analytics, and content performance products.
• Take proprietary audience and creator models from feature engineering and training through to production deployment and monitoring.
• Apply statistical rigour to extract actionable insight from large, complex, often unstructured datasets.
• Work hands‑on with LLMs and foundation models - fine‑tuning, prompt engineering, RAG, and other post-training techniques.
• Partner with business leaders to ensure statistical rigour underpins reporting and decision-support tools.
• Contribute to the team's intellectual culture via technical blogs, internal research, and conference talks.

• Building and shipping ML/statistical models in production - not just notebooks.
• Strong Python fluency across the modern data science stack (PyTorch, Tensor Flow, scikit-learn, or equivalent).
• Operating at scale: large datasets, complex pipelines, and the engineering challenges that come with them.
• Working with LLMs/foundation models and applying frontier ML research to real business problems.

• You approach problems from first principles and interrogate whether a model is the right tool before reaching for one.
• You're intellectually rigorous and honest - careful experiment design, appropriate scepticism, clear communication of uncertainty.
• You think of data as a strategic asset and connect technical work to the business questions it answers.
• You're energised by hard, ambiguous problems in messy, real-world environments - you don't need a clean brief to do great work.
• You're a builder first: you get models into production, not just into a deck.
• You're high ownership, low ego, and commercially minded.
• You're intellectually curious - you read research, build outside of work, and bring fresh thinking to the team.

• Demonstrable experience building and deploying ML or statistical models in production.
• Strong Python and relevant DS library experience.
• Background in consumer/enterprise data products, creator economy, or media analytics is a strong advantage.
• Bonus: CS/ML research background, agentic AI or multi-model architecture experience, creator/audience/community data exposure, published research or open-source contributions, or time at organisations at the frontier of applied AI.