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

Apply Now

Data Science Lead

System Recruitment Limited
Southampton
4 months ago
Applications closed

Related Jobs

View all jobs

Data Science Lead

Data Science/Analytics Lead – Private Credit/Asset Based Finance/Securitization

Data Science/Analytics Lead – Private Credit/Asset Based Finance/Securitization

Senior Data Scientist

Lead Data Engineer

Senior Data Scientist

IT Jobs Southampton, England £75000 - £80000 per annum Permanent Apply Now

Data Science Lead

A small but growing specialist company specialising in high tech detection solutions have an immediate requirement for a Data Science Lead to join them.


Location: Southampton 1 day per week – rest can be home based.


Salary: Circa £75,000


Key Skills: Data Science Lead, data analysis, linear regression, time-series, classification, neural networks, CNNs, RNNs, decision trees, gradient boosting, Python, C/C , Unix shell scripting, Java, JavaScript/HTML/CSS/Angular, RDBMS,


This is a new role for the company and they are keen to find an experienced and motivated data professional.


As Data Science Lead you will develop a deep understanding of the customer and a passion for solving real world problems. As Data Science Lead you will be responsible for championing the adoption of data driven decisions across the company by leading the development of advanced analytical tools that utilise the vast amounts of data available to the company. These tools will be rooted in a strong statistical foundation and leverage Machine Learning to provide actionable insights for solving business problems or finding opportunities for profitable growth.


As a Lead, you will work with the Engineering Director, to steer the company in the most profitable direction while also implementing its vision, mission and long-term goals. Strong communication, delegation, coaching and leadership skills are required as you will be expected to lead the department in times of need and growth.


AS Data Science Lead you will:


* Work with the team to solve complex business problems by implementing end-to-end AI/ML capabilities: from data exploration, model training and validation to model persistence and deployment of productionised machine learning models.
* Show-case the “Art of the Possible” through the establishment and engagement with the team of innovative data science standards and methodologies: developing scalable and sustainable solutions for diverse business segments; incorporating emerging technologies into data analysis processes and influencing the scope and direction of new projects.
* Work with the team, to conduct advanced statistical analyses of structured and unstructured datasets using a variety of modelling techniques, such as: linear regression, time-series, classification, neural networks (incl. CNNs, RNNs), decision trees, gradient boosting, and others to deploy interpretable products that generate insights, increase efficiency and/or enhance quality.
* Understand existing business processes and combine business acumen, problem solving skills, and curiosity to identify value-add opportunities for the applications of statistical analyses and AI/Machine Learning.
* Present results in a cohesive, intuitive, and concise manner that can be understood by both technical and non-technical audiences.
* Provide expertise on statistical and mathematical concepts to key stakeholders.
* Act as a subject matter expert in Data Science approach and design discussions.


Key Skills


* Experience of lead roles in medium or large physics or software projects


* Excellent presentation and communication skills


Key Knowledge


* Numerate degree or equivalent tertiary education
* Relevant postgraduate qualification: MSc, PhD or equivalent – ideally Physics
* Knowledge and solid experience of relevant languages. In rough order of importance: Python, C/C , Unix shell scripting, Java, JavaScript/HTML/CSS/Angular.
* Knowledge and solid experience of one or more relevant machine learning frameworks. E.g. Scikit-learn, TensorFlow, PyTorch.
* Knowledge and experience of data management technologies. E.g. RDBMS
* Knowledge and experience of object-oriented development principles and patterns.
* Knowledge and experience of working in Linux/Unix.
* Knowledge and experience of production software development tools, such as configuration management, issue trackers, build engines, installer tools, cloud services, container technologies.
* Any experience nuclear detection devices would be a benefit.


Needless to say, if you have got this far then please click “apply now” for more details about the role and company.

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.