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- Tasks: Lead the design and development of AI models for product discovery.
- Company: Fast-growing early-stage AI company revolutionising consumer recommendations.
- Benefits: Competitive salary, bonuses, equity options, and a chance to shape the future.
- Other info: Collaborative environment with significant career growth potential.
- Why this job: Make a real impact in AI and influence product direction from day one.
- Qualifications: Experience in search, ranking, retrieval, or recommendation systems required.
The predicted salary is between 43200 - 72000 £ per year.
We are working with a fast growing early stage company that is building a new intelligence layer for the next era of product discovery. With AI assistants becoming the first place consumers turn to for information and recommendations, brands need to understand how these systems interpret products, surface them and prioritise them across different conversational and search environments. This is exactly what this company solves.
They already partner with global consumer brands and now want to hire a Lead Data Scientist to architect and own the modelling engine that powers the platform. This is a hands-on role with serious technical ownership. You will design and build the systems that identify the signals that matter most for visibility, the retrieval and embedding architecture that feeds the models, the ranking and scoring framework that prioritises actions and the evaluation layer that measures how different LLMs behave across queries, surfaces and contexts.
You will work across ranking signals, vector and semantic representations, entity understanding, graph-based relationships, model serving, observability, cost and latency optimisation, and the connection between unstructured signals and automated recommendations. You will also help shape the long-term ML strategy, including platform design, experimentation frameworks and the future of the discovery engine.
This role suits someone who has experience in search, ranking, retrieval or recommendation systems at scale and who enjoys building practical production models rather than working in isolation. You will work closely with the founder and have real influence over the direction of the product and the future of the intelligence stack.
The package is strong and comes with a competitive base plus bonus and meaningful early-stage equity with genuine upside. If you are interested in joining a company at a stage where your work will directly shape the product, the system and the category, we would like to speak with you.
Lead Data Scientist employer: Zazu Digital Talent
Contact Detail:
Zazu Digital Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to search, ranking, and retrieval systems. This hands-on evidence of your expertise can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by diving deep into the company's tech stack and recent projects. Tailor your questions and answers to show how your experience aligns with their needs—this shows you're genuinely interested and ready to contribute.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're proactive and keen on joining the team.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Lead Data Scientist role. Highlight your experience in search, ranking, and retrieval systems, as well as any hands-on projects you've worked on that showcase your technical ownership.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you the perfect fit for our team. Don’t forget to mention specific projects or achievements that relate to the job description.
Showcase Your Technical Skills: In your application, be sure to include examples of your work with modelling engines, ranking frameworks, and any relevant ML strategies you've developed. We want to see how you’ve tackled challenges in the past and what tools you used to achieve success.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company and culture!
How to prepare for a job interview at Zazu Digital Talent
✨Know Your Stuff
Make sure you brush up on your knowledge of search, ranking, retrieval, and recommendation systems. Be ready to discuss your hands-on experience with these technologies and how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in previous roles and how you tackled them. This is a hands-on role, so demonstrating your ability to architect and build effective models will be key.
✨Understand the Company’s Vision
Familiarise yourself with the company’s mission and the impact of their AI solutions on product discovery. Being able to articulate how your skills align with their goals will show that you're genuinely interested in the role.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's current projects, future direction, and the specifics of the modelling engine you'll be working on. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.