Head of Data Science
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-02-28
Listing for:
Propel
Full Time
position Listed on 2026-02-28
Job specializations:
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Science Manager, Data Analyst
Job Description & How to Apply Below
🚀 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
- Personally design, build and deploy production computer vision and agentic AI systems powering search, discovery, recommendations and personalisation
- Make pragmatic trade-offs between speed, quality and technical elegance
- 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
- 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)
- Build scalable but lightweight pipelines (AWS)
- Ensure models are robust, reliable, explainable where needed and safe in production
- 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
- 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
- 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
- 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
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