Senior Data Scientist - UK

Infused Solutions
United Kingdom
3 weeks ago
£60,000 – £70,000 pa

Salary

£60,000 – £70,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
Remote
Seniority
Senior
Education
Degree
Posted
8 May 2026 (3 weeks ago)

Benefits

Fully remote UK-based role Opportunity to work on cutting-edge AI and machine learning products Collaborative, research-driven environment Exposure to modern AI, NLP, and cloud technologies Strong career development opportunities within a growing AI function

Senior Data Scientist

Location: UK Remote

Salary: £60,000 - £70,000

Employment Type: Full-Time

Please note: Sponsorship is not available for this position.

Overview

A growing organisation is looking for a Senior Data Scientist to help develop advanced AI and analytics capabilities that power large-scale intelligence and data-driven products.

This is an opportunity to work within a research-focused environment, building scalable machine learning models and AI systems across areas such as NLP, recommendation systems, predictive analytics, and workforce intelligence.

The Role

As a Senior Data Scientist, you will contribute to the development and optimisation of advanced machine learning and AI models while maintaining high standards of experimentation, validation, and responsible AI practices.

You'll work closely with AI Engineers, Product teams, and cross-functional stakeholders to deliver scalable, production-ready solutions that drive measurable business value.

Key Responsibilities

Develop and refine machine learning models across NLP, classification, prediction, optimisation, and recommendation systems

Apply generative AI and NLP techniques to improve modelling and data extraction capabilities

Perform large-scale data analysis and transformation using SQL and cloud-native technologies

Design and execute experimentation, benchmarking, and model validation frameworks

Translate business and product challenges into scalable, data-driven solutions

Collaborate with Engineering teams to productionise models and APIs

Maintain best practices across reproducibility, explainability, and responsible AI

Contribute to the development of knowledge-based and ontology-driven systems

Required Skills & Experience

Strong commercial experience in Data Science, Machine Learning, or Advanced Analytics

Strong Python and SQL skills

Experience building models across NLP, prediction, optimisation, classification, or recommender systems

Familiarity with embeddings, LLMs, and prompt engineering

Experience working within AWS and/or Azure cloud environments

Understanding of experimentation design, model validation, and reproducibility best practices

Experience supporting model deployment into production environments

Strong analytical and problem-solving skills

Excellent communication and stakeholder engagement skills

Technology Stack

Python, SQL, Databricks, PyTorch, Transformers/LLMs, Prompt Engineering, Pandas, Spark, AWS, Azure, PostgreSQL, FastAPI, Git, CI/CD, Knowledge Graphs

What's on Offer

Fully remote UK-based role

Opportunity to work on cutting-edge AI and machine learning products

Collaborative, research-driven environment

Exposure to modern AI, NLP, and cloud technologies

Strong career development opportunities within a growing AI function

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Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.