

Coltech
Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Scientist contract (long-term, inside IR35) based in London (hybrid, 2 days onsite), requiring 10+ years in Data Science, strong Python skills, and experience with machine learning, NLP, and Generative AI solutions.
π - Country
United Kingdom
π± - Currency
Β£ GBP
-
π° - Day rate
Unknown
-
ποΈ - Date
March 18, 2026
π - Duration
More than 6 months
-
ποΈ - Location
Hybrid
-
π - Contract
Inside IR35
-
π - Security
Unknown
-
π - Location detailed
London Area, United Kingdom
-
π§ - Skills detailed
#BigQuery #AI (Artificial Intelligence) #Azure #NLP (Natural Language Processing) #GCP (Google Cloud Platform) #ML (Machine Learning) #Cloud #Python #AWS (Amazon Web Services) #Data Science #Leadership #Scala
Role description
Data Scientist (Machine Learning & Generative AI) β Contract
π London (Hybrid β 2 days onsite)
πΌ Long-term Contract (Inside IR35)
The Opportunity
Weβre hiring multiple Data Scientists to join a major, enterprise-scale programme focused on machine learning and Generative AI innovation.
This is a long-term contract opportunity where youβll work on real-world, production-grade AI solutions, including LLM-powered applications, NLP pipelines, and emerging agentic systems.
Youβll be operating in a highly data-driven environment, solving complex business problems and delivering impactful AI use cases at scale.
Key Responsibilities
β’ Build, deploy, and optimise machine learning and NLP models in production
β’ Develop end-to-end data science pipelines
β’ Design and prototype Generative AI solutions (LLMs, embeddings, prompt engineering)
β’ Work with BigQuery ML and cloud platforms for large-scale modelling
β’ Translate business challenges into scalable data solutions
β’ Collaborate with cross-functional teams across engineering and business
β’ Mentor junior team members where required
Required Experience
β’ 10+ years in Data Science, Machine Learning, or AI Engineering
β’ Strong Python skills and experience with ML frameworks
β’ Proven track record delivering end-to-end ML/NLP solutions
β’ Hands-on experience with Generative AI (LLMs, embeddings, prompting)
β’ Experience with cloud platforms (GCP, AWS, or Azure)
β’ Exposure to BigQuery ML or similar platforms
Preferred Experience
β’ Background in financial services or regulated environments
β’ Experience with fraud, risk, or customer analytics
β’ Exposure to LLM applications or agentic AI systems
β’ Mentoring or leadership experience
Data Scientist (Machine Learning & Generative AI) β Contract
π London (Hybrid β 2 days onsite)
πΌ Long-term Contract (Inside IR35)
The Opportunity
Weβre hiring multiple Data Scientists to join a major, enterprise-scale programme focused on machine learning and Generative AI innovation.
This is a long-term contract opportunity where youβll work on real-world, production-grade AI solutions, including LLM-powered applications, NLP pipelines, and emerging agentic systems.
Youβll be operating in a highly data-driven environment, solving complex business problems and delivering impactful AI use cases at scale.
Key Responsibilities
β’ Build, deploy, and optimise machine learning and NLP models in production
β’ Develop end-to-end data science pipelines
β’ Design and prototype Generative AI solutions (LLMs, embeddings, prompt engineering)
β’ Work with BigQuery ML and cloud platforms for large-scale modelling
β’ Translate business challenges into scalable data solutions
β’ Collaborate with cross-functional teams across engineering and business
β’ Mentor junior team members where required
Required Experience
β’ 10+ years in Data Science, Machine Learning, or AI Engineering
β’ Strong Python skills and experience with ML frameworks
β’ Proven track record delivering end-to-end ML/NLP solutions
β’ Hands-on experience with Generative AI (LLMs, embeddings, prompting)
β’ Experience with cloud platforms (GCP, AWS, or Azure)
β’ Exposure to BigQuery ML or similar platforms
Preferred Experience
β’ Background in financial services or regulated environments
β’ Experience with fraud, risk, or customer analytics
β’ Exposure to LLM applications or agentic AI systems
β’ Mentoring or leadership experience






