At a Glance
- Tasks: Design and build AI systems that make a real impact in business processes.
- Company: Dynamic media business in Central London, focused on AI innovation.
- Benefits: Competitive daily rate, flexible contract, and opportunity to work on cutting-edge projects.
- Other info: Join a team that values innovation and offers excellent career growth.
- Why this job: Shape the future of AI while working independently in a fast-paced environment.
- Qualifications: Strong experience in machine learning, AI systems, and Python engineering.
6 months’ initial contract £500- £600 pd outside IR35 3 days Central London
Job Overview
Stanton House has partnered with a media business based in Central London, that is looking to hire an Interim Data Scientist / AI Engineer. Our client is building out a new data science and AI function focused on developing AI agent capabilities and embedding AI into business processes. This role will play a key part in shaping and delivering production-grade AI systems. This is a hands-on contract role suited to someone who can operate independently, take ownership, and deliver high-impact AI solutions in a fast-evolving environment.
Responsibilities
- Design and build LLM-powered AI agents and multi-agent systems for real-world business applications
- Develop agentic workflows, incorporating RAG, reasoning, planning, and tool orchestration
- Build and deploy production-grade GenAI systems, not just prototypes
- Integrate AI solutions into existing business systems, APIs, and workflows
- Contribute to or establish MLOps frameworks (e.g. Databricks or similar environments)
- Work closely with stakeholders to translate business problems into technical AI solutions
- Own delivery end-to-end, operating with minimal supervision
- Communicate complex technical concepts clearly to non-technical stakeholders
Skills Needed
- Strong experience delivering machine learning and AI systems
- Strong expertise in LLMs, Generative AI, and RAG systems
- Proven experience building AI agents / agentic systems
- Hands-on experience with LangGraph and/or similar frameworks
- Strong Python engineering skills with experience building scalable systems
- Experience with MLOps and ML platforming (e.g. Databricks or equivalent)
- Experience designing and deploying systems on cloud platforms (AWS preferred)
- Strong understanding of system design, orchestration, and production constraints
- Ability to work independently, take ownership, and proactively drive work forward
- Strong communication skills, with the ability to engage stakeholders and translate technical detail into business context
Data Scientist employer: Stanton House
Stanton House offers an exceptional work environment for Data Scientists, particularly in the vibrant setting of Central London. With a focus on innovation and cutting-edge AI solutions, employees benefit from a culture that encourages independence and ownership, alongside opportunities for professional growth in a rapidly evolving field. The competitive contract rates and the chance to work on impactful projects make this an attractive opportunity for those seeking meaningful and rewarding employment.
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 data science field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to someone looking for a Data Scientist.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and Generative AI. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex technical concepts in simple terms, as you'll need to engage with non-technical stakeholders. We want you to shine!
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of exciting roles that could be perfect for you. Plus, applying directly can sometimes give you an edge over other candidates.
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 machine learning, AI systems, and any relevant projects you've worked on. We want to see how your skills match 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 the perfect fit for this role. Mention specific experiences that relate to building AI agents and integrating solutions into business processes. Let us know your passion for AI!
Showcase Your Technical Skills:In your application, don't forget to showcase your technical skills, especially in Python and MLOps. We love seeing hands-on experience, so mention any frameworks like LangGraph or cloud platforms like AWS that you've worked with.
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, we love seeing applications come directly from our site!
How to prepare for a job interview at Stanton House
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, Generative AI, and RAG systems. Be ready to discuss your hands-on experience with these technologies and how you've applied them in real-world scenarios. This will show that you’re not just familiar with the concepts but can also deliver practical solutions.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific projects where you’ve translated complex business problems into AI solutions. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting your role in the project and the impact of your work.
✨Communicate Like a Pro
Since you'll need to engage with non-technical stakeholders, practice explaining complex technical concepts in simple terms. Think about how you would describe your work to someone without a tech background, and be ready to demonstrate this during the interview.
✨Be Ready for Hands-On Challenges
Expect some practical assessments or case studies during the interview. Brush up on your Python skills and be prepared to discuss how you would build and deploy production-grade AI systems. Show that you can think critically and operate independently in a fast-paced environment.
