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

Apply Now

Lead Data Scientist

City of London
3 weeks ago
Create job alert

Partnered with a global Legal Services orgnisation who are searching for Permanent Lead Data Scientist to play a key role within the Product Function leading the development of enterprise grade Data solutions and advanced analytics capabilities.

Scope of role:

Play a key role to developing firms AI strategy and roadmap.
Develop and implement Data Science and analytics use cases aligning Business priorities.
Design and deploy predictive models and AI/ML prototypes
Buils robustand interpretable models for forcasting, clustering and optimisation.
Act as the Lead on solution design and prototyping of advanced analytics solutions.
Enable good governance principles across analytics delivery.Experience required:

Experienced in delivering end to end Analytics Solutions.
Strong Python, SQL, PowerBI.
Legal or regulatory background preferred.
Stakeholder experience, comfortable dealing with various Senior level stakeholders.
Experience leading teams or technical projects.

If this opportunity aligns with your background and career aspirations please share your details to (url removed) , your latest CV and availability for a call

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist - Remote

Lead Data Scientist – NLP

Lead Data Scientist

Lead Data Scientist

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 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.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.