We're supporting a growing engineering business looking to hire a Data Scientist to help develop scalable ML and AI solutions across compliance, risk and contractor analytics platforms.

You'll work closely with AI Engineers, Data Engineers and DevOps teams to build and deploy predictive models and LLM-powered solutions in production environments across AWS and Azure.

This is a hands-on opportunity to work on modern AI and machine learning initiatives that directly support operational performance, compliance and risk management. You'll be involved in the full model lifecycle from data ingestion and feature engineering through to deployment, optimisation and monitoring.

• Develop machine learning models for risk scoring, churn prediction and contractor analytics
• Build LLM and NLP solutions for automated compliance checks and insight generation
• Deploy AI and ML models into cloud-based production environments
• Work with Microsoft Fabric for data ingestion, transformation and feature engineering
• Improve model monitoring, retraining and optimisation processes
• Collaborate closely with engineering and product teams in agile delivery squads
• Communicate technical solutions clearly to non-technical stakeholders
• Contribute to best practices around coding standards, maintainability and AI-assisted development

Python, SQL, TensorFlow, PyTorch, AWS, Azure, Microsoft Fabric, NLP, LLMs, MLOps

• Strong commercial Data Science experience
• Experience building and deploying ML models into production
• Strong understanding of predictive modelling, NLP and LLM architectures
• Cloud experience with AWS and/or Azure
• Experience with Python, SQL and modern ML frameworks
• Strong communication and stakeholder management skills
• Ability to work collaboratively in agile engineering teams

• Risk modelling or compliance analytics
• Supply chain or operational analytics
• MLOps and CI/CD pipelines
• Data governance or regulatory environments

You'll join a collaborative engineering environment working on genuinely impactful AI projects with modern tooling and cloud technologies. This is an opportunity to help shape the future direction of AI capability within a growing business while working on real-world applications of LLMs and predictive analytics.