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

Apply Now

Data Scientist (eDV clearance required)

London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist Python Software - London (IT) / Freelance

Our client, a leading company in the Defence & Security sector, is currently seeking a data-driven and passionate Data Scientist with eDV clearance to join their team. This permanent position offers the opportunity to work on complex data problems and deliver innovative solutions that drive real impact.

Key Responsibilities:

Leading client projects and providing subject matter expertise.
Working in scrum-like environments for iterative and 'fail-fast' work and innovation.
Assessing clients' business and technical needs to identify opportunities for data science usage.
Solving problems using data science techniques and in a scientifically robust fashion.
Identifying relevant data sources and leveraging them to meet client needs.
Modelling various forms of data for efficient data science use.
Investigating and analysing data to uncover meaningful insights.
Applying statistical and evidence-based techniques to inform insights and actions.
Communicating technical content appropriately both internally and to customers.
Building maintainable code using existing or novel data science techniques.
Designing, evaluating, and implementing data science and machine learning techniques.
Developing scalable models and algorithms for deployment in production environments.
Applying ethical principles in handling data.
Delivering high-quality work to agreed timelines and taking the initiative.
Supporting client engagements, including pitches and presentations.
Contributing to the company strategy and helping to shape the future.

Job Requirements:

DV Cleared (2023, 2024, 2025) or holding DV Clearance.
Experience in data science, machine learning algorithms, and data engineering.
Industry experience in consultancy, engineering, or data science.
Significant experience with cloud-based infrastructure (e.g., AWS, Azure, GCP).
Proficiency in Python and relevant data science libraries.
Experience in using CI/CD tooling for code deployment and testing.
Knowledge of database technologies (e.g., SQL, NoSQL such as Elasticsearch and Graph databases).
Understanding of coding best practices, design patterns, and versioning.
Strong interpersonal skills and the ability to communicate effectively with clients and colleagues.

Benefits:

Joining a dynamic and agile organisation.
Opportunities for professional growth and development.
Working in an environment that values transparency, fairness, and daring.
Collaborative and respectful work environment.
Hybrid working model with 2-3 days in the office or on a client site.
If you are a skilled Data Scientist with the necessary clearance and a passion for technology and problem-solving, we would love to hear from you. Apply now to join our client's innovative and forward-thinking team

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.