National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Lead Data Science Engineer

Matchtech
Worcestershire
1 week ago
Create job alert

Job summary

Our client, a leading provider of software solutions to the insurance industry, is seeking aLead Data Science Engineerto join their growing Data & Analytics team.

Key skills required for this role

Head Of Data

Important

Head of Data

Job description

Key Responsibilities:


Lead the design and implementation of scalable data infrastructure for machine learning, analytics, and reporting.




Develop and launch secure APIs and DaaS solutions.




Deploy production-ready ML models and manage their lifecycle.




Promote data governance and quality standards across the platform.




Collaborate with cross-functional teams to translate business challenges into technical solutions.


Tech Stack Includes:Python, SQL, Azure, Postgres, Langchain, Ollama, Polars, GitLab CI/CD, Systemd, Ansible


Ideal Candidate Profile:


Significant experience as a Data Science or ML Engineer, with leadership responsibilities.




Strong Python skills and experience with cloud-based data platforms (preferably Azure).




Proven success deploying ML models into production.




Solid understanding of data privacy, governance, and API development.




Excellent communication skills and stakeholder engagement abilities.


Bonus Points For:


Experience in insurance or financial services.




Familiarity with Docker, Kubernetes, or infrastructure-as-code tools.


Share

manages this role

Matchtech is a STEM Recruitment Specialist, with over 40 years’ experience

Related Jobs

View all jobs

Lead Data Science Engineer

Lead Data Science Engineer

Lead Data Science Engineer

Technical Lead - Data Science & Engineering

▷ [3 Days Left] Lead Data Science Engineer...

Technical Lead (Data Science)

National AI Awards 2025

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 Jobs Skills Radar 2026: Emerging Tools, Frameworks & Platforms to Learn Now

Machine learning is no longer confined to academic research—it's embedded in how UK companies detect fraud, recommend content, automate processes & forecast risk. But with model complexity rising and LLMs transforming workflows, employers are demanding new skills from machine learning professionals. Welcome to the Machine Learning Jobs Skills Radar 2026—your annual guide to the top languages, frameworks, platforms & tools shaping machine learning roles in the UK. Whether you're an aspiring ML engineer or a mid-career data scientist, this radar shows what to learn now to stay job-ready in 2026.

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.