Data Scientist (Assistant Manager/Manager)

This is an opportunity to join a growing Simulation & Insights team working at the intersection of data science, AI and decision modelling.

You'll be delivering solutions that help organisations make complex, high-value decisions, from optimising operations to shaping long-term strategy.

It's a hands-on role with a strong consulting edge. You'll be building models one day and working directly with stakeholders the next, explaining what the outputs actually mean for the business.

The role is offered at Assistant Manager or Manager level, depending on experience. At Manager level, you'll take on additional ownership of projects, stakeholders and team members.

What You'll Do

• Build and deploy data science, machine learning and simulation models to solve complex business problems

• Apply advanced techniques including optimisation, forecasting, statistical modelling and AI

• Develop LLM-based solutions, including:

• Retrieval-Augmented Generation (RAG)

• Fine-tuning and prompt engineering

• Agent-based workflows

Work with large and complex datasets, both structured and unstructured

Write clean, scalable Python code for model development and production use

Use tools such as Databricks, MLflow and modern AI platforms to manage the full model lifecycle

Translate technical outputs into clear, commercially relevant insights

Engage directly with stakeholders to define problems and shape solutions

Collaborate with multidisciplinary teams across data, engineering and strategy

At Manager level, you will also:

• Lead projects or workstreams end-to-end
• Manage and mentor junior team members
• Own stakeholder relationships and present to senior audiences
• Contribute to business development and proposition building, * Work on high-impact projects that directly influence business decisions
• Exposure to cutting-edge AI and LLM use cases
• Variety of work across multiple industries and problem types
• Clear progression from Assistant Manager to Manager and beyond
• Strong focus on learning, development and career progression
• Hybrid working model with flexibility built in
• Collaborative team environment with high-performing peers

• Strong academic background in a STEM discipline
• Proven experience delivering data science, machine learning or AI solutions in a commercial environment
• Strong programming capability in Python (Pandas, NumPy, SciPy or similar)
• Solid grounding in statistics, probability and data analysis

AI & LLM Experience

• Hands-on experience with large language models, including:

• RAG pipelines

• Fine-tuning approaches

• Agent-based architectures

A practical understanding of how to apply LLMs to real-world use cases

Tools & Engineering

• Experience with model deployment and MLOps tools (e.g. Databricks, MLflow)
• Familiarity with version control (Git) and collaborative development practices
• Awareness of best practices in code quality and reproducibility

Communication & Consulting

• Ability to explain complex technical concepts to non-technical stakeholders
• Experience working in client-facing or cross-functional teams
• Strong problem-solving skills and the ability to manage ambiguity