Job description:
Role Title: Data and AI Scientist
Division: Data Analytics
Location: Liverpool or London
Contract: Perm
Working pattern: Hybrid
About the Role
Deliver transformational Data Science, AI, and GenAI solutions across the organisation to drive measurable business value and pioneer the use of this advanced technology in Rathbones
This role will shape the strategic direction of Data Science at Rathbones, lead high-impact projects from concept to production and will partner with stakeholders across the business to solve business problems of all styles and sizes.
What you'll be responsible for
Grow and develop a leading Data Science capability aligned to the Group Data Strategy
Deliver production‑ready ML, AI and GenAI solutions with clear business impact
Embed modern Data Science and MLOps standards across the organisation
Build, develop and lead a high‑performing Data Science team
Influence senior stakeholders to adopt data‑driven decision making
Deliver transformational Data Science, AI, and GenAI solutions across the organisation to drive measurable business value and pioneer the use of this advanced technology in Rathbones
Lead the design, development and productionisation of machine learning, AI and GenAI solutions that deliver measurable business value
Partner with stakeholders across Wealth and Enablement to identify and prioritise high impact opportunities for data science and advanced analytics
Champion modern Data Science and MLOps practices, ensuring repeatable, scalable and high quality solution delivery
Work collaboratively with Data Engineering, Data Operations and Architecture teams to ensure seamless integration and performance of models in production
Provide thought leadership on emerging AI, ML and GenAI techniques championing innovation and experimentation
Define technical standard, best practice and governance for Data Science across Rathbones
Mentor, coach and develop Data Scientists to build a high performing innovative team
Communicate complex technical concepts clearly to senior stakeholders, influencing adoption of data-driven decision making
About you
If you meet some of these criteria and are excited about the role, we encourage you to apply.
Advanced Python skills including environments, packaging and production-grade coding
Strong SQL and experience working with large-scale analytical datasets
Hand-on experience with cloudplatforms including Azure, AWS and Snowflake
Expertise in machine learning frameworks and libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow)
Deep understanding of GenAI concepts including LLMs, prompt engineering, RAG, embeddings, vector databases and model evaluation
Experience building end-to-end ML and GenAI solutions, from experimentation to production
MLOps tooling experience (Mlflow, feature stores, CI/CD pipelines, containerisation, model monitoring)
Understanding of data engineering concepts, data pipelines, orchestration (Fivetran, Airflow, Azure Data factory), and model deployment patterns
Experience with visualisation tools (PowerBI, Plotly, customer dashboards) to communicate insights
Familiarity with software engineering best practices (version control, testing, documentation, code review)
Ability to translate unstructured business problems into analytical and MI/AI solutions
Strong communication and stakeholder management skills across all levels
Demonstrated leadership and ability to develop technical teams
Strong problem solving, curiosity and passion for experimentation
Experience working in financial services, ideally wealth or asset management