Head of Data Science📍 Flexible / Hybrid | Early-Stage | High Impact🚀 The Future of Fashion DiscoveryAs 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 buildWhat not to buildWhen “good enough” is the right answerWhat You’ll Own🔬 Hands-on AI & Data LeadershipPersonally design, build and deploy production computer vision and agentic AI systems powering search, discovery, recommendations and personalisationOwn the full lifecycle: problem framing → data exploration → modelling → evaluation → deployment → monitoring → iterationMake pragmatic trade-offs between speed, quality and technical elegance🎯 Product & User ImpactTranslate messy user problems into clear, testable interventionsPartner deeply with Product to optimise for trust, confidence and discovery — not just offline metricsFocus relentlessly on feature value and ROI🧱 Data FoundationsWork hands-on with imperfect datasetsDesign annotation strategies, quality checks and evaluation frameworks from scratchDecide where data investment matters — and where it doesn’t (yet)⚙️ Technical Direction & MLOpsEstablish 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 & CultureSet a strong technical and ethical bar for data scienceMentor future hires as the team growsModel curiosity, humility and ownership in high ambiguity🛡 Ethics, Bias & Brand TrustProactively address bias, representation and fairness in AI systemsAlign technical decisions with company values around individuality and body confidenceSpeak up when technical direction risks user trust🤖 Internal AI Adoption (Critical)Evaluate and drive adoption of AI productivity tools across Product & EngineeringEmbed AI-assisted development into day-to-day workflowsDefine standards that let us move fast — without building tech debt mountainsMust-Haves3–5 years in a technical leadership roleProven track record delivering AI/ML products from inception to productionDeep 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 systemsStrong MLOps and engineering mindsetHands-on with AWS, Python, SQL and modern ML toolingStrong data engineering and annotation strategy experienceExperience leading teams and working with senior stakeholdersComfortable in fast-moving, evolving environmentsSimplicity mindset: start simple, add complexity only when necessary