Senior Data Scientist

Overview

As a Senior Data Scientist at AJ Bell, you will convert complex, ill-defined business questions into clear, actionable insights. You’ll apply Python, SQL, and statistical methods to explain what happened, why, and what may occur next, while engaging with senior stakeholders. Your analyses drive practical decisions, risk assessment, and opportunity identification to support business goals. This role suits someone who thrives in ambiguity and helps others act on data-driven conclusions. You will shape solutions with cross-functional teams and deliver impactful, accessible findings.

Pay / Benefits

• 26 days holiday, increasing with service
• 7% pension with matched contributions
• Discretionary bonus scheme
• Share schemes, including free shares and BAYE
• Health Cash Plan and discounted private healthcare
• Free onsite gym

Responsibilities

• Turn ambiguous business questions into robust analyses and actionable insights
• Use Python and SQL for data analysis and modelling
• Apply statistical and data-science techniques to business problems (forecasting, regression, classification, segmentation, propensity modelling)
• Assess model performance, bias, and uncertainty, and communicate implications to senior stakeholders
• Collaborate with stakeholders to define requirements, explore data, and translate findings into practical actions
• Deliver concise conclusions and commercial implications suitable for decision-making
• Iterate quickly, prioritise effectively, and provide initial answers without waiting for perfectly defined requirements

Key requirements

• Significant experience as Data Analyst, Senior Data Analyst, Data Scientist, Insight Analyst or equivalent
• Strong analytical and problem-solving skills with ability to clarify ambiguous questions
• Advanced Python skills for data analysis and modelling, plus strong SQL
• Experience applying statistical and data-science techniques to business problems (forecasting, regression, classification, segmentation, propensity modelling)
• Understanding of statistical concepts, model evaluation, uncertainty, bias and limitations
• Experience with large/complex datasets, data discovery, validation, and exploratory analysis
• Excellent requirements gathering, stakeholder management, and project planning
• Excellent written communication with experience for senior audiences
• Ability to translate complex analysis into concise conclusions, implications and actions
• Ability to iterate quickly, prioritise effectively, and provide initial answers with imperfect data

• Curiosity
• Commercial mindset
• Strong stakeholder-management
• Python for data analysis and modelling
• SQL
• Statistical methods (forecasting, regression, classification, segmentation, propensity modelling)

…