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- Tasks: Lead AI experiments and design solutions that drive business success.
- Company: Join a high-performing AI System Design team focused on innovation.
- Benefits: Earn up to £475/day with remote work flexibility.
- Why this job: Make a real impact by building production-level AI systems.
- Qualifications: 5+ years in Data Science, with 2+ years in Generative AI.
- Other info: Interviews happening this week for a mid-senior level contract role.
The predicted salary is between 100000 - 140000 £ per year.
We’re looking for a Generative AI Data Scientist to join a high-performing AI System Design team working on cutting‑edge LLM, agentic workflows, and enterprise‑scale AI architectures. If you enjoy building real production AI systems — not just prototypes — this role is for you.
What you’ll be working on:
- Leading end-to-end AI experiments from idea → design → deployment
- Designing AI solutions that tie directly to business KPIs & measurable outcomes
- Architecting data pipelines & AI workflows on Azure + Databricks
- Working hands‑on with LLMs, RAG, fine‑tuning, multi‑agent workflows
- Using toolkits like PyTorch, LangChain, LangGraph, MCP, Hugging Face
- Building automated AI evaluation, monitoring & MLOps frameworks
- Communicating AI decisions clearly to technical and non‑technical teams
Requirements:
- 5+ years in Data Science, incl. 2+ years in Generative AI/LLMs
- Ability to link AI design → business value
Nice to have:
- Experience with multi‑agent AI architectures
- Open‑source or publication contributions
Remote (UK-based) | Contract | Mid‑Senior level
Data Scientist employer: Careerwise
Contact Detail:
Careerwise Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and Data Science fields. Attend meetups, webinars, or even online forums. You never know who might have the inside scoop on job openings or can refer you directly!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and generative AI. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Practice explaining complex AI concepts in simple terms. Remember, you’ll need to communicate effectively with both techies and non-techies alike!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Data Scientists like you. Plus, it’s a great way to ensure your application gets seen by the right people!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Science and Generative AI. We want to see how your skills link directly to the role, so don’t be shy about showcasing relevant projects and achievements!
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 a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Technical Skills: Since we’re working with cutting-edge tech like LLMs and Azure, make sure to mention any hands-on experience you have with these tools. We’re looking for someone who can hit the ground running, so highlight those technical skills!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Careerwise
✨Know Your AI Stuff
Make sure you brush up on your knowledge of generative AI and LLMs. Be ready to discuss your past projects in detail, especially those that involved real production systems. Highlight how your work has directly impacted business KPIs.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in AI experiments and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it clear how your solutions added value.
✨Familiarise Yourself with Tools
Get comfortable with the tools mentioned in the job description, like PyTorch and Azure. If you’ve used similar technologies, be ready to explain how they relate and how quickly you can adapt to new ones.
✨Communicate Clearly
Practice explaining complex AI concepts in simple terms. You’ll need to communicate effectively with both technical and non-technical teams, so think about how you can make your insights accessible to everyone.
