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

Apply Now

Data Science Specialist

Areti Group | B Corp
London
2 days ago
Create job alert

Job Title: Data Consultants - Multiple Positions ranging from Junior to Senior Principal
Location: London (Hybrid – Flexible working with client site travel required)
Salary: Competitive, based on experience (from 1 year to Principal level) -Multiple positions required
Leading consultancy partner headquartered in London
Focused on delivering data solutions that drive measurable business impact

Broad role spanning data science, engineering, analytics, and strategy
Design, implement, and optimize end-to-end data solutions
Work on high-impact, dynamic projects with flexibility to innovate

Translate client challenges into actionable data solutions
Develop and deploy scalable data pipelines and architectures
Perform data analysis, modeling, and machine learning tasks
Advise on data governance, compliance, and best practices
Collaborate across multidisciplinary teams to deliver project goals
1+ years’ experience in a data-related role (Analyst, Engineer, Scientist, Consultant, or Specialist)
~ Experience with technologies such as Python, SQL, Spark, Power BI, AWS, Azure, or GCP
~

Related Jobs

View all jobs

Data Science Specialist

AI & Data Science Specialist (m/f/d)

AI & Data Science Specialist (m/f/d)

Sport Scientist (Human Data Science)

Applied AI & Data Scientist

Applied AI & 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.