Data Scientist - Gen AI

Vallum Associates
Sheffield, South Yorkshire, United Kingdom
3 weeks ago
£525 – £550 pd
Applications closed

Related Jobs

View all jobs
Spotlight

Machine Learning Engineer - National Security (Gloucestershire)

Mind Foundry Gloucester, Gloucestershire, United Kingdom
On-site Clearance Required

Data Scientist

Faculty AI London, United Kingdom
Hybrid

Data Scientist

Guidant Global London, United Kingdom
£600 – £850 pd On-site Clearance Required

Data Scientist

Hays Technology London, United Kingdom
£600 – £1,000 pd

Data Scientist

ISR Recruitment Exeter, Devon, United Kingdom
£50,000 – £60,000 pa Hybrid

Data Scientist

Advertising Standard Authority Old Street, London, United Kingdom
£45,000 – £60,000 pa Hybrid

Data Scientist

Randstad Technologies Recruitment London, United Kingdom

Salary

£525 – £550 pd

Posted
20 Apr 2026 (3 weeks ago)

A Data Scientist with banking experience designs predictive models, analyzes financial data, and develops ML/NLP solutions for risk management, fraud detection, and customer analytics. Key responsibilities include building credit risk scorecards, automating data pipelines, and ensuring regulatory compliance, typically requiring 3–5+ years of experience with Python, SQL, and statistical modeling in financial institutions.

Key Responsibilities

* Predictive Modeling & Analytics: Develop behavioural segments, credit risk scorecards, and predictive models for customer onboarding, cross-selling, and churn retention.

* Fraud & Risk Management: Utilize advanced analytics to identify anomalies and fraudulent activities in transaction data. Implement risk models (probability of default) and maintain regulatory compliance.

* Data Handling: Extract, clean, and analyze structured and unstructured data from internal/external sources.

* Technology & Tools: Write advanced SQL queries and Python/R scripts for data manipulation and build machine learning algorithms (e.g., Scikit-learn, TensorFlow).

* Stakeholder Communication: Translate complex analytical findings into actionable business insights for management.

Required Experience & Skills

* Domain Expertise: 3+ years of experience in banking or financial services, specifically in credit risk, fraud strategy, or compliance.

Need candidates with 3–8 years’ experience in GenAI/Data Science, strong in Python, LLMs (RAG/fine-tuning), NLP, ML model deployment (MLOps), and cloud (AWS/Azure/GCP), with proven delivery in enterprise use cases

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

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.

Machine Learning Jobs UK 2026: What to Expect Over the Next 3 Years

Machine Learning Jobs UK 2026: roles, salaries and the MLOps, LLM and generative AI hiring trends shaping UK ML careers over the next three years. Machine learning has undergone a transformation that few technology disciplines can match. In the space of three years it has moved from a specialism sitting at the edges of most organisations' technology strategies to a capability that sits at the centre of them. The tools have changed, the expectations have shifted, and the range of industries treating machine learning as a core business function — rather than an experimental one — has expanded dramatically. For job seekers, this creates both opportunity and complexity in roughly equal measure. The machine learning jobs market of 2026 is significantly larger than it was three years ago, but it is also significantly more demanding. Employers have developed more sophisticated expectations, the technical bar for specialist roles has risen, and the landscape of tools, frameworks, and architectural patterns that practitioners are expected to know has broadened considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what machine learning engineers and researchers are expected to build, and how the definition of a machine learning career is evolving beyond the model-building core toward a much wider range of roles across the full ML lifecycle. This article breaks down what the UK machine learning jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.