SC Cleared AI Data Scientist

The successful candidate will combine strong data science expertise with hands-on experience across machine learning, Generative AI and Large Language Models (LLMs). You will work closely with multidisciplinary teams to rapidly assess ideas, develop proofs of concept and provide evidence-based recommendations that shape future investment and delivery decisions., * Conduct AI discovery, research and feasibility assessments.

• Analyse data sets, business processes and operational challenges to identify opportunities for AI adoption.
• Develop, test and evaluate machine learning and Generative AI prototypes.
• Design evaluation frameworks and performance benchmarks for AI solutions.
• Produce clear technical findings, insights and recommendations.
• Collaborate with engineers, architects, delivery teams and business stakeholders.
• Contribute to reusable assets, standards and best practice frameworks.
• Support Responsible AI, governance and assurance activities.
• Assist delivery teams in refining and improving AI solutions through experimentation and testing.

• Active SC Clearance.
• Strong experience using modern data science tools, techniques and methodologies.
• Proven knowledge of machine learning, Generative AI and prompt engineering.
• Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI evaluation approaches.
• Strong data analysis, visualisation and statistical modelling skills.
• Experience managing AI experimentation and model evaluation activities.
• Understanding of Responsible AI principles, ethics and data governance.
• Familiarity with cloud-based AI and data platforms.
• Excellent analytical and problem-solving capabilities.
• Strong communication skills with the ability to explain complex technical concepts to non-technical audiences.

Personal Attributes

• Analytical and inquisitive mindset.
• Comfortable working with ambiguity and evolving requirements.
• Strong attention to detail and evidence-based decision making.
• Collaborative and team-oriented approach.
• Ability to balance technical depth with business value.
• Driven by outcomes and continuous improvement.