Head of Data Science Flexible / Hybrid | Early-Stage | High Impact The Future of Fashion Discovery As a female-founded startup at an exciting inflection point, we’re shaping something genuinely game-changing. This isn’t just a product. It’s a movement. And we’re looking for a brilliant Head of Data Science to help lead the charge. You’ll own and build the intelligence at the heart of the platform — personally designing, building, deploying and iterating on production AI systems while shaping long-term data and AI strategy. You’ll work shoulder-to-shoulder with founders, product and engineering to decide: What to build What not to build When “good enough” is the right answer What You’ll Own Hands-on AI & Data Leadership Personally design, build and deploy production computer vision and agentic AI systems powering search, discovery, recommendations and personalisation Own the full lifecycle: problem framing → data exploration → modelling → evaluation → deployment → monitoring → iteration Make pragmatic trade-offs between speed, quality and technical elegance Product & User Impact Translate messy user problems into clear, testable interventions Partner deeply with Product to optimise for trust, confidence and discovery — not just offline metrics Focus relentlessly on feature value and ROI Data Foundations Work hands-on with imperfect datasets Design annotation strategies, quality checks and evaluation frameworks from scratch Decide where data investment matters — and where it doesn’t (yet) ⚙️ Technical Direction & MLOps Establish pragmatic MLOps practices (CI/CD, deployment, monitoring, alerting) Build scalable but lightweight pipelines (AWS) Ensure models are robust, reliable, explainable where needed and safe in production Team & Culture Set a strong technical and ethical bar for data science Mentor future hires as the team grows Model curiosity, humility and ownership in high ambiguity Ethics, Bias & Brand Trust Proactively address bias, representation and fairness in AI systems Align technical decisions with company values around individuality and body confidence Speak up when technical direction risks user trust Internal AI Adoption (Critical) Evaluate and drive adoption of AI productivity tools across Product & Engineering Embed AI-assisted development into day-to-day workflows Define standards that let us move fast — without building tech debt mountains Must-Haves 3–5 years in a technical leadership role Proven track record delivering AI/ML products from inception to production Deep hands-on expertise in at least one core ML domain (strong preference for computer vision and/or generative AI) Experience with LLMs, conversational AI and evaluation of generative systems Strong MLOps and engineering mindset Hands-on with AWS, Python, SQL and modern ML tooling Strong data engineering and annotation strategy experience Experience leading teams and working with senior stakeholders Comfortable in fast-moving, evolving environments Simplicity mindset: start simple, add complexity only when necessary