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

Apply Now

Data Scientist

City of London
3 weeks ago
Create job alert

Data Scientist - data and analytics

+6 months

+Fully remote working

+Inside IR35

+£450 - £525 a day

We're looking for an experienced Data Scientist to play a key role in turning complex data into clear, actionable insights. You'll be responsible for the full data lifecycle - from collection and cleaning to analysis, modelling, and communication of findings - ensuring all work aligns with project objectives and timelines. This is a highly collaborative role, working closely with our existing team to deliver high-quality results and meet project deadlines.

The role:

Collect, clean, and preprocess structured and unstructured data from multiple internal and external sources.
Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
Design and implement data pipelines for model-ready datasets in collaboration with data engineering teams.
Apply feature engineering and selection techniques to improve model accuracy and interpretability.
Develop and validate machine learning and statistical models for prediction, classification, clustering, or optimization.
Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch.
Implement NLP, time-series forecasting, or optimization algorithms based on project requirements.
Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance.
Convert proof-of-concept models into production-grade pipelines in collaboration with MLOps and engineering teams.Required:

Translate model outcomes into actionable insights through clear storytelling and visualizations.
Build dashboards and reports using Power BI, Tableau, or Python-based visualization tools.
Communicate findings to both technical and non-technical stakeholders effectively.
Partner with business analysts, architects, and domain experts to define use cases and success metrics.
Contribute to the enterprise AI roadmap, bringing thought leadership on analytical methodologies.
Document methodologies, model logic, and validation results for audit and reproducibility.
Participate in Agile ceremonies, sprint planning, and client showcases.If you'd like to discuss this data scientist role in more detail, please send your updated CV to (url removed) and I will get in touch

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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 Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.