

Lorien
Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a 6-month contract, paying "competitive rate," based in London (Hybrid). Key skills include Python, LLM systems, AI agents, and cloud deployment. A Master's in a relevant field is required.
π - Country
United Kingdom
π± - Currency
Β£ GBP
-
π° - Day rate
Unknown
-
ποΈ - Date
April 11, 2026
π - Duration
More than 6 months
-
ποΈ - Location
Hybrid
-
π - Contract
Outside IR35
-
π - Security
Unknown
-
π - Location detailed
London Area, United Kingdom
-
π§ - Skills detailed
#Deployment #AI (Artificial Intelligence) #Cloud #Classification #Azure #FastAPI #Data Science #SaaS (Software as a Service) #GCP (Google Cloud Platform) #Computer Science #Datasets #"ETL (Extract #Transform #Load)" #Forecasting #Langchain #ML (Machine Learning) #Python #Scala #AWS (Amazon Web Services)
Role description
Data Scientist / Machine Learning Scientist - Outside IR35
Location: London (Hybrid)
Length: 6 months
Ready to build and deploy real AI systems at scale?
Join a growing AI teams, where youβll shape how AI transforms global business. Weβre hiring hands-on operators who deliver production-ready LLM and agentic solutionsβnot just prototypes.
What Youβll Do:
β’ Design and build AI agents and agentic workflows powered by LLMs (retrieval, reasoning, tool orchestration)
β’ Develop multi-step intelligent systems for planning, memory, and real-world tool usage
β’ Deliver recommendation, classification, and forecasting systems on large-scale datasets
β’ Automate complex workflows and decision-making, driving measurable business impact
β’ Own problems end-to-end: from exploration to production deployment and iteration
β’ Integrate AI into products, APIs, and business processes for scalable, reliable solutions
β’ Collaborate with engineering to ensure robust, observable, and maintainable systems
What Youβll Bring:
β’ Strong Python skills and production-grade coding experience
β’ Proven track record shipping LLM-powered systems (LangChain/LangGraph or similar) into production
β’ Hands-on experience with AI agents, agentic workflows, and multi-step reasoning
β’ Experience designing and implementing RAG systems with real-world impact
β’ Familiarity with MCP or similar orchestration patterns (FastMCP/FastAPI)
β’ Understanding of LLM limitations and trade-offs (hallucination, latency, cost)
β’ Cloud deployment experience (AWS, GCP, Azure)
β’ Masters or higher in Maths, Science, or Computer Science
β’ Ownership mindset, bias for action, and strong product focus
β’ Comfortable in fast-moving, ambiguous environments
Bonus Points:
β’ Experience with SaaS/B2B AI products or AI-driven business transformation
β’ Background in high-growth/scaling environments
β’ Evidence of systems delivering real value in production
Data Scientist / Machine Learning Scientist - Outside IR35
Location: London (Hybrid)
Length: 6 months
Ready to build and deploy real AI systems at scale?
Join a growing AI teams, where youβll shape how AI transforms global business. Weβre hiring hands-on operators who deliver production-ready LLM and agentic solutionsβnot just prototypes.
What Youβll Do:
β’ Design and build AI agents and agentic workflows powered by LLMs (retrieval, reasoning, tool orchestration)
β’ Develop multi-step intelligent systems for planning, memory, and real-world tool usage
β’ Deliver recommendation, classification, and forecasting systems on large-scale datasets
β’ Automate complex workflows and decision-making, driving measurable business impact
β’ Own problems end-to-end: from exploration to production deployment and iteration
β’ Integrate AI into products, APIs, and business processes for scalable, reliable solutions
β’ Collaborate with engineering to ensure robust, observable, and maintainable systems
What Youβll Bring:
β’ Strong Python skills and production-grade coding experience
β’ Proven track record shipping LLM-powered systems (LangChain/LangGraph or similar) into production
β’ Hands-on experience with AI agents, agentic workflows, and multi-step reasoning
β’ Experience designing and implementing RAG systems with real-world impact
β’ Familiarity with MCP or similar orchestration patterns (FastMCP/FastAPI)
β’ Understanding of LLM limitations and trade-offs (hallucination, latency, cost)
β’ Cloud deployment experience (AWS, GCP, Azure)
β’ Masters or higher in Maths, Science, or Computer Science
β’ Ownership mindset, bias for action, and strong product focus
β’ Comfortable in fast-moving, ambiguous environments
Bonus Points:
β’ Experience with SaaS/B2B AI products or AI-driven business transformation
β’ Background in high-growth/scaling environments
β’ Evidence of systems delivering real value in production






