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