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For Companies At a Glance
- Tasks: Design and scale cloud-native AI services and APIs for enterprise-wide adoption.
- Company: Join a forward-thinking company at the forefront of AI innovation.
- Benefits: Competitive pay, hybrid work, and opportunities for professional growth.
- Why this job: Work on cutting-edge AI systems and make a real impact in a global R&D environment.
- Qualifications: 7+ years as a Data Scientist with strong Python skills and AI experience.
- Other info: Collaborative Scrum team with a focus on continuous learning and mentorship.
The predicted salary is between 36000 - 60000 £ per year.
About the Role
Outside IR35 £200 – £300
Initial 6 month contract – high possibility of 18 months
Hybrid work
Our client is hiring a Data Scientist – AI/ML Engineer to join our Core AI Services team. You’ll be at the forefront of designing and scaling cloud-native AI platform services and APIs that enable enterprise-wide AI adoption. Working within a collaborative Scrum team, you’ll help build secure, reliable, and production-grade AI solutions that are ethical, scalable, and future-ready.
This is a unique opportunity to work on cutting-edge AI systems in a global R&D environment, contributing to the development of trustworthy AI services.
About the Role:
DataBuzz is hiring a Data Scientist – AI/ML Engineer to join our Core AI Services team. You\’ll design and scale cloud-native AI platform services and APIs that power enterprise AI adoption. Working in a Scrum team with developers, architects, and data scientists, you\’ll build secure, reliable, and production-grade AI solutions. If you\’re passionate about solving complex challenges and advancing cutting-edge AI, this role is for you.
Skills & Experience:
- 7+ Years of experience as a Data Scientist or in a similar role.
- Strong programming skills in Python are essential, including libraries such as pandas, scikit-learn, TensorFlow, or PyTorch.
- Experience working with Large Language Models (LLMs).
- Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling
- Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A)
- Experience in working with various ML algorithms (regression, classification, clustering, deep learning)
- Familiarity with Azure cloud platform.
- Strong problem-solving skills and the ability to explain technical concepts to non-technical audiences are important.
What You\’ll Do:
- Build scalable, fault-tolerant cloud-native services on Microsoft Azure.
- Develop secure, well-documented APIs and SDKs for developers inside and outside the organisation.
- Collaborate with teams to deliver end-to-end data pipelines, orchestration, and service APIs.
- Embed security best practices around authentication, authorization, and data privacy.
- Take part in design reviews, code reviews, and architecture discussions to ensure excellence.
- Deploy and manage AI models and tooling for enterprise-scale adoption.
- Mentor junior developers and foster a culture of continuous learning and innovation.
Data Scientist employer: Opus Recruitment Solutions
Contact Detail:
Opus Recruitment Solutions 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 community. 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 AI/ML. Use platforms like GitHub to share your code and document your thought process. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data science interview questions and coding challenges. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, applying directly can sometimes give you an edge over other candidates. So, get your application in and let’s get you that dream job!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with AI/ML, especially your programming skills in Python and any relevant projects you've worked on. We want to see how your background aligns with what we're looking for!
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 skills can contribute to our Core AI Services team. Keep it engaging and personal – we love getting to know the real you!
Showcase Your Projects: If you've worked on any cool AI projects, make sure to mention them! Whether it's using Large Language Models or developing APIs, we want to see your hands-on experience. Include links to your GitHub or portfolio if you have them!
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 get all the updates directly from us. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Opus Recruitment Solutions
✨Know Your Tech Inside Out
Make sure you brush up on your programming skills, especially in Python and the libraries mentioned like pandas and TensorFlow. Be ready to discuss your experience with Large Language Models and how you've applied them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex challenges you've tackled in your previous roles. Think about how you approached these problems and the impact your solutions had on the project or team.
✨Understand the Company’s AI Vision
Research DataBuzz and their approach to AI. Familiarise yourself with their Core AI Services team and be prepared to discuss how your skills align with their goals, particularly around ethical and scalable AI solutions.
✨Practice Explaining Technical Concepts
Since you'll need to communicate with non-technical audiences, practice explaining your work in simple terms. This will show your ability to bridge the gap between technical and non-technical stakeholders, which is crucial for this role.
