Senior Data Scientist – AI/ML & Generative AI

At CGI, our Data Scientists turn advanced AI and machine learning into solutions that create meaningful outcomes for clients. As a Senior Data Scientist, you will take ownership of developing and deploying production-ready AI/ML solutions, helping organisations harness emerging technologies including Generative AI. Working alongside a collaborative community of data, cloud and technology specialists, you will have the freedom to explore new approaches while applying strong engineering principles to deliver scalable, trusted solutions. From shaping ideas and experimenting with models to deploying them in AWS environments, you will influence technical direction, share your expertise and continue developing your capabilities while helping CGI and our clients realise greater value from data and AI.



CGI was recognised in the Sunday Times Best Places to Work List 2025 and has been named a UK ‘Best Employer’ by the Financial Times. We offer a competitive salary, excellent pension, private healthcare, plus a share scheme (3.5% + 3.5% matching) which makes you a CGI Partner not just an employee. We are committed to inclusivity, building a genuinely diverse community of tech talent and inspiring everyone to pursue careers in our sector, including our Armed Forces, and are proud to hold a Gold Award in recognition of our support of the Armed Forces Corporate Covenant. Join us and you’ll be part of an open, friendly community of experts. We’ll train and support you in taking your career wherever you want it to go.



Due to the secure nature of the programme, you will need to hold UK Security Clearance or be eligible to go through this clearance. This role is based on site in Gloucester full time.

Profil recherché

In this role, you will take ownership of developing AI and machine learning solutions throughout the data science lifecycle, from experimentation and model development through to deployment and continuous improvement. You will apply your knowledge of AI/ML, including emerging Generative AI capabilities, to solve complex challenges and help deliver scalable solutions that create measurable value.



You will combine data science expertise with strong software engineering practices, working with AWS, containerisation and Kubernetes to move models successfully into production. Supported by CGI’s wider community of experts, you will have opportunities to explore new technologies, influence technical approaches and collaborate with multidisciplinary teams to build robust and maintainable AI solutions.



Key responsibilities



Develop & Deliver: Build, test and deploy machine learning and AI solutions that address complex requirements.



Innovate & Explore: Evaluate emerging AI/ML developments, including Generative AI, and identify opportunities to apply them effectively.



Own & Optimise: Contribute throughout the data science and MLOps lifecycle, continuously improving model performance and reliability.



Engineer & Automate: Apply software engineering, version control and unit-testing practices to create maintainable production solutions.



Cloud & Scale: Develop and deploy workloads using AWS and cloud-native technologies.



Containerise & Deploy: Use Docker, microservice architectures and Kubernetes, particularly AWS EKS, to operationalise AI/ML solutions.



Collaborate & Share: Work alongside data, engineering and cloud specialists, sharing knowledge and contributing to technical direction.

Required qualifications to be successful in this role

You should bring strong practical experience in data science and machine learning, supported by sound software engineering and cloud skills. You will be comfortable taking AI/ML solutions beyond experimentation and into production, with knowledge of MLOps, AWS and modern deployment approaches. You should also maintain a strong awareness of developments across AI, including Generative AI, and be able to work collaboratively with technical teams in a full-time, site-based environment in Gloucester.



Data Science & ML: Strong experience across the data science and machine learning lifecycle.



AI/ML Expertise: Strong understanding of current AI/ML approaches and emerging trends, including Generative AI.



ML Frameworks: Practical experience with machine learning libraries and frameworks such as PyTorch, TensorFlow and NumPy.



MLOps: Familiarity with MLOps practices and tooling for developing, deploying and maintaining machine learning solutions.



Software Engineering: Good software development practices, including version control and unit testing.



AWS: Practical experience developing or deploying solutions within Amazon Web Services.



Containers: Experience or strong familiarity with Docker and containerised applications.



Kubernetes: Experience deploying workloads to Kubernetes, ideally Amazon EKS.



Architecture: Understanding of microservice architectures and scalable production environments.



Collaboration: Strong communication skills and the ability to contribute effectively within multidisciplinary technical teams.



Location: Able to work full time on site in Gloucester.