

La Fosse
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist position for a 6-month contract in London, offering £575 per day. Key skills include Python, LLM deployment, and experience with AWS, Azure, or GCP. Proven experience in production AI systems is essential.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
575
-
🗓️ - Date
May 8, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Outside IR35
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#AWS (Amazon Web Services) #GCP (Google Cloud Platform) #"ETL (Extract #Transform #Load)" #AI (Artificial Intelligence) #SaaS (Software as a Service) #Azure #Scala #Data Science #FastAPI #Langchain #Cloud #Python
Role description
🚨 CONTRACT OPPORTUNITY – DATA SCIENTIST 🚨
📍 London (Hybrid)
🏢 FTSE 100 Business
💰 £575 per day
🧾 Outside IR35
📆 6-Month Initial Contract
A leading FTSE 100 organisation is building out multiple AI teams focused on both AI product development and enterprise-wide AI transformation initiatives.
This is a production-first environment focused on deploying AI systems that are actively used, trusted, and continuously improved - not experimental proof-of-concepts.
Candidates should have proven experience building and deploying real-world LLM and agentic systems into production environments at scale.
Key Responsibilities:
• Designing and building AI agents and agentic workflows powered by LLMs
• Developing multi-step intelligent systems incorporating reasoning, planning, memory, and tool orchestration
• Building and improving RAG pipelines and retrieval systems
• Working with MCP-style architectures / FastMCP / FastAPI
• Automating complex workflows and decision-making processes using AI
• Deploying scalable AI systems into production cloud environments
Required Experience:
• Strong Python engineering skills with production-grade coding standards
• Proven experience shipping LLM-powered applications into production
• Hands-on experience with LangChain / LangGraph or similar frameworks
• Experience building AI agents with orchestration and tool usage
• Strong understanding of RAG architectures and LLM trade-offs
• Experience deploying systems across AWS, Azure, or GCP
• Strong product mindset with a bias toward delivery and impact
Additional Desirable Experience:
• SaaS or B2B AI product environments
• High-growth or scaling businesses
• Evidence of AI systems actively delivering measurable business value
🚨 CONTRACT OPPORTUNITY – DATA SCIENTIST 🚨
📍 London (Hybrid)
🏢 FTSE 100 Business
💰 £575 per day
🧾 Outside IR35
📆 6-Month Initial Contract
A leading FTSE 100 organisation is building out multiple AI teams focused on both AI product development and enterprise-wide AI transformation initiatives.
This is a production-first environment focused on deploying AI systems that are actively used, trusted, and continuously improved - not experimental proof-of-concepts.
Candidates should have proven experience building and deploying real-world LLM and agentic systems into production environments at scale.
Key Responsibilities:
• Designing and building AI agents and agentic workflows powered by LLMs
• Developing multi-step intelligent systems incorporating reasoning, planning, memory, and tool orchestration
• Building and improving RAG pipelines and retrieval systems
• Working with MCP-style architectures / FastMCP / FastAPI
• Automating complex workflows and decision-making processes using AI
• Deploying scalable AI systems into production cloud environments
Required Experience:
• Strong Python engineering skills with production-grade coding standards
• Proven experience shipping LLM-powered applications into production
• Hands-on experience with LangChain / LangGraph or similar frameworks
• Experience building AI agents with orchestration and tool usage
• Strong understanding of RAG architectures and LLM trade-offs
• Experience deploying systems across AWS, Azure, or GCP
• Strong product mindset with a bias toward delivery and impact
Additional Desirable Experience:
• SaaS or B2B AI product environments
• High-growth or scaling businesses
• Evidence of AI systems actively delivering measurable business value






