At a Glance
- 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 remote work flexibility.
- Why this job: Shape the future of AI-driven product discovery and make a real impact.
- Qualifications: Experience in search, ranking, retrieval, or recommendation systems.
- Other info: Collaborate closely with the founder and influence product direction.
The predicted salary is between 36000 - 60000 Β£ 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 in Warrington employer: Zazu Digital Talent
Contact Detail:
Zazu Digital Talent Recruiting Team
StudySmarter Expert Advice π€«
We think this is how you could land Lead Data Scientist in Warrington
β¨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 a job description just can't.
β¨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.
β¨Tip Number 3
Prepare for interviews by diving deep into the company's products and their tech stack. Understand how they use AI and be ready to discuss how your experience aligns with their needs. We want to see your passion and knowledge!
β¨Tip Number 4
Apply through our website! Itβs the best way to ensure your application gets seen. Plus, it shows youβre genuinely interested in joining us and being part of our exciting journey in shaping the future of product discovery.
We think you need these skills to ace Lead Data Scientist in Warrington
Some tips for your application π«‘
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience with search, ranking, and retrieval systems, and donβt forget to showcase any hands-on projects that demonstrate your technical ownership.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why youβre excited about this early-stage AI company and how your skills align with their mission. Be genuine and let your passion for AI and product discovery come through.
Showcase Relevant Projects: If you've worked on any relevant projects, make sure to mention them in your application. Whether it's building models or optimising systems, we want to see how you've tackled challenges similar to what we face at StudySmarter.
Apply Through Our Website: We encourage you to apply directly through our website. Itβs the best way for us to receive your application and ensures youβre considered for the role. Plus, it shows youβre keen on joining our team!
How to prepare for a job interview at Zazu Digital Talent
β¨Know Your Stuff
Make sure you brush up on your knowledge of search, ranking, retrieval, and recommendation systems. Be ready to discuss your past experiences and how they relate to the role. Prepare specific examples of projects you've worked on that demonstrate your technical skills and ownership.
β¨Understand the Companyβs Vision
Dive deep into the companyβs mission and the problems theyβre solving with their AI products. Familiarise yourself with their current partnerships and how they leverage AI for product discovery. This will help you align your answers with their goals and show that youβre genuinely interested in contributing to their success.
β¨Prepare for Technical Questions
Expect to face some challenging technical questions during the interview. Brush up on your knowledge of modelling engines, vector representations, and evaluation layers. Practise explaining complex concepts in a simple way, as this will demonstrate your ability to communicate effectively with both technical and non-technical stakeholders.
β¨Show Your Collaborative Spirit
This role involves working closely with the founder and influencing product direction, so be prepared to discuss your experience in collaborative environments. Share examples of how youβve successfully worked in teams, contributed to discussions, and helped shape project outcomes. Highlight your enthusiasm for building practical models in a hands-on role.