Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Scientist - Outside IR35

London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

2x Data Scientist
£475 - £500 outside IR35 p/d
6 months initial - likely to extend
Once a week into London

SR2 are supporting a major cross-government digital initiative focused on transforming how citizens interact with government services through AI. The team is developing an intelligent tool that understands when a user requires human assistance and seamlessly connects them to the most appropriate support route across departments.

This project sits at the intersection of agentic AI, conversational systems, and government service delivery, and aims to reduce the knowledge burden on users by creating a single, intelligent entry point for government support.

The Role
As a Data Scientist, you’ll play a pivotal role in designing, experimenting, and validating new AI models that enhance the performance and human-routing logic of the platform. You’ll work in a multidisciplinary environment alongside developers, researchers, and policy experts, helping shape the direction of a national-scale AI service.

Key Responsibilities
Identify and define key technical research questions, and run rapid experiments to validate assumptions in the AI domain.
Develop, evaluate, and optimise conversational AI models, including Retrieval-Augmented Generation (RAG) architectures.
Implement and refine LLM-as-a-judge evaluation frameworks for continuous model improvement.
Collaborate closely with cross-functional teams to translate business challenges into analytical and data-driven solutions.
Produce clear, visually compelling analytical outputs to inform decision-making at senior levels.
Develop Python-based analytical pipelines and prototype models in a cloud environment (AWS preferred).
Contribute to integration efforts between AI systems and existing digital service platforms.Skills & Experience Required
Proven experience as a Data Scientist, with hands-on capability in Python and applied AI experimentation.
Experience in cloud-based environments (AWS preferred).
Practical experience with conversational AI and RAG system optimisation.
Strong stakeholder engagement skills, able to explain complex AI/ML concepts to non-technical audiences.
Demonstrable ability to design analytical outputs that support business and policy decisions.
Background in collaborative, agile environments delivering data-driven value.Desirable
Experience working with agentic AI frameworks in an experimental or applied context.
Familiarity with Model Context Protocol (MCP).
Exposure to CRM systems or human support integration use cases

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.