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 £ 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 Chesterfield 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 in Chesterfield
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to search, ranking, and retrieval systems. We want to see your hands-on experience and how you’ve tackled real-world problems.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and being ready to discuss your past work. We recommend practising common data science interview questions and even doing mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Lead Data Scientist in Chesterfield
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Lead Data Scientist. Highlight your experience with search, ranking, and retrieval systems, and don’t 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 you’re excited about this role and how your skills align with the company’s mission. Be genuine and let your passion for AI and product discovery come through.
Showcase Relevant Projects: If you've worked on projects related to LLM modelling or recommendation systems, make sure to include them in your application. We love seeing practical examples of your work that demonstrate your ability to build impactful models.
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 this exciting opportunity to shape the future of our intelligence stack!
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 past experiences and how they relate to the role. We recommend preparing specific examples of projects you've worked on that showcase your technical skills and problem-solving abilities.
✨Understand the Company’s Vision
Dive deep into the company’s mission and the products they’re developing. Familiarise yourself with their current partnerships and how they leverage AI for product discovery. This will not only help you answer questions but also allow you to ask insightful ones, showing your genuine interest in their work.
✨Prepare for Technical Questions
Expect to face some challenging technical questions during the interview. We suggest practising coding problems or system design scenarios related to LLMs and data architecture. Being able to articulate your thought process clearly will demonstrate your hands-on experience and technical ownership.
✨Show Your Collaborative Spirit
This role involves working closely with the founder and other team members, so it’s crucial to highlight your teamwork skills. Share examples of how you’ve successfully collaborated on projects in the past, especially in fast-paced environments. We want to see that you can contribute to shaping the product and the team dynamic.