As an Associate Data Scientist you will be instrumental in developing and deploying large language model (LLM) applications, design, build and maintain robust cloud hosted data pipelines, and creating interactive dashboards and visual reports to support decision making. Our team has a unique blend of data science, software engineering and cloud infrastructure components, giving you the opportunity to take projects from initial concept through model development and testing, to full-scale deployment. We are looking for proactive, self-starting candidates who are keen to broaden their skills, embrace software engineering best practices, and deepen their understanding of cloud technologies. This is an exciting opportunity to support innovative work within government. You’ll be helping to harness the power of data and AI to shape the UK’s future in digital transformation, driving evidence-based decisions that deliver real societal impact. At DSIT, you’ll join a collaborative and inclusive environment where diverse perspectives are valued, and where you can thrive, grow, and make a difference. As an Associate Data Scientist you’ll: design, develop, and maintain LLM-powered applications, ensuring scalable and robust AI solutions design, build, and optimise cloud-hosted ETL workflows for both structured and unstructured data explore and deliver proof-of-concepts for emerging AI technologies, evaluating their business value and practical applications collaborate with stakeholders to identify and deliver impactful AI use cases across the organisation create clear, compelling, and interactive visualisations that communicate complex data insights to both technical and non-technical audiences gather and refine reporting requirements, tailoring data visualisation solutions to meet stakeholder needs engage with programme leads and stakeholders to ensure analytical approaches are appropriate and outputs meet end-user expectations present, document, and communicate analytical findings to key decision-makers in a clear and actionable way actively contribute to team learning and your own continuous professional development (CPD), aligning with organisational goals work within Agile, multidisciplinary teams to deliver data science solutions, defining minimum viable products (MVPs) and iterating based on user needs
