Principal Data Scientist

Birmingham, United Kingdom / Brighton, United Kingdom / Bristol, United Kingdom / Cardiff, United Kingdom / Glasgow, United Kingdom / London, United Kingdom / Manchester, United Kingdom / Newcastle Upon Tyne, United Kingdom

Location/s: London, Cardiff, Bristol, Brighton, Birmingham, Manchester, Glasgow, Newcastle
Relocation supported:Not supported, but internal applications are welcome
Hiring manager contact: Sam Ahdab

Mott Mac Donald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices.

We work across incredible global industries, delivering exciting work that is defining our future and making an important societal impact in the communities we serve. Our people power our performance – we succeed when they do. With countless opportunities to collaborate, learn, and grow, the possibilities for excellence are as varied as every individual.

Whether you want to grow as a subject matter expert or broaden your experience with roles across our international community, you’re surrounded by global specialists who want to combine their expertise and champion you to be your best. As a proudly employee‑owned business, we benefit our clients, our communities, and each other, investing in creating the right space for everyone to feel empowered, included, and valued.

Whatever your ambition, Mott Mac Donald is where people come to be brilliant.

We are looking for a Principal Data Scientist to help shape the design, development and delivery of production‑grade AI, machine learning and data science solutions across Mott Mac Donald. The role will focus on turning complex business, engineering and environmental needs into scalable, reliable data products and AI services.

The successful candidate will bring technical experience across generative AI, large language models, retrieval augmented generation, machine learning, computer vision, geospatial data science and MLOps. They will work with multidisciplinary teams to identify valuable use cases, shape solution architecture, develop reliable models and ensure solutions are tested, monitored and improved in live use.

The role includes end‑to‑end AI and data science delivery; setting standards for model development, evaluation and deployment; building reusable internal AI services; coaching data scientists and engineers; contributing to AI governance; and translating technical opportunities into clear business value for project teams and senior stakeholders.

• Experience delivering production data science, machine learning or AI in an enterprise environment.
• Practical experience in Python and modern machine learning frameworks such as PyTorch, Tensor Flow or Keras.
• Practical experience with generative AI, large language models, embedding models, retrieval augmented generation, AI agents, model evaluation and fine‑tuning techniques.
• Experience designing and operating end‑to‑end MLOps workflows, including model training, deployment, monitoring, automation and continuous improvement.
• Ability to work across cloud and engineering environments, including tools such as Azure, Kubernetes, Docker, MLflow, Git Hub Actions, Terraform or Databricks.
• Clear communication and stakeholder engagement skills, with the ability to explain complex technical concepts in accessible business language.
• Experience coaching, mentoring or giving technical guidance to data scientists, machine learning engineers or data professionals
• Experience applying computer vision, geospatial data science or predictive modelling to engineering, infrastructure, environmental or asset management work.
• Knowledge of tools and methods such as Lang Chain, LLM orchestration, agentic tool use, segmentation foundation models, zero/few‑shot visual understanding
• Experience developing reusable internal AI platforms, foundation‑model services or automation capabilities for use by wider teams.
• Postgraduate qualification or equivalent research experience in data science, engineering, computer science, applied mathematics or a related discipline.
• Evidence of innovation, publication, award recognition or…