Senior Data Scientist

Overview

As Senior Data Scientist at AJ Bell, you translate complex, often vague business questions into actionable insights. You will lead high-value analytics using Python, SQL and statistical methods to explain trends, predict outcomes, and inform decisions. You’ll work closely with senior stakeholders to ensure clarity and relevance, turning analysis into practical actions. This role sits at the intersection of data science and business strategy, shaping how information drives investment decisions. You will operate in a fast-paced, collaborative environment with a strong emphasis on impact and clear communication.

Pay / Benefits

• 26 days holiday
• 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

• Lead high-value analytical work using Python, SQL, and statistical methods to explain trends and forecast outcomes
• Translate analysis results into practical recommendations for senior stakeholders
• Engage with cross-functional stakeholders to clarify questions and align on objectives
• Produce concise, decision-focused outputs (papers/recommendations) for senior audiences
• Iterate quickly to provide useful initial answers even with imperfect requirements
• Manage project planning and requirements gathering in analytics initiatives

Key requirements

• Significant experience as Data Analyst, Senior Data Analyst, Data Scientist, Insight Analyst or equivalent
• Strong analytical and problem-solving abilities with the ability to turn ambiguity into clarity
• Advanced Python skills for data analysis and modelling; strong SQL capability
• Practical 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 of analyses
• Experience with large/complex datasets and data discovery, validation, and exploratory analysis
• Excellent requirements gathering, stakeholder-management and project-planning skills
• Excellent written communication with experience producing analytical recommendations for senior audiences
• Ability to translate complex analysis into concise conclusions, commercial implications and actions
• Ability to iterate quickly and provide useful initial answers without waiting for perfectly defined requirements

• Curious
• Commercially minded
• Analytical
• Python for data analysis and modelling
• SQL
• Statistical techniques (forecasting, regression, classification, segmentation, propensity modelling)

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