The Data Analyst role is responsible for unlocking value from data by making complex information accessible, meaningful and actionable for stakeholders across the organisation. The role transforms data into insights that support strategic decision-making, optimise operations and drive business performance.

Requirements

Key Responsibilities

• Conduct advanced data analysis across multiple business areas to identify trends, patterns, opportunities and potential data issues.
  
• Translate complex analytical findings into clear business insights and recommendations for technical and non-technical stakeholders.
  
• Lead data analysis projects, taking ownership of planning, scoping, timelines, delivery and quality.
  
• Develop and maintain KPIs, reports, forecasting, scenario analysis and dashboards to support informed decision-making.
  
• Apply advanced statistical techniques and develop simple predictive models, following appropriate data science and analytical lifecycles.
  
• Work closely with business and technical teams to understand requirements, data flows, processes and downstream data needs.
  
• Act as a bridge between business stakeholders, data analysts, engineers and data scientists.
  
• Challenge assumptions, vague requirements and requests that may not address the underlying business need.
  
• Identify opportunities to improve processes, data assets and analytical ways of working.
  
• Ensure data analysis is accurate, well documented, repeatable and suitable for implementation with minimal rework.
  
• Support data modelling and data mart development, ensuring data can be effectively used across multiple teams.
  
• Identify and address data quality gaps and proactively challenge solution designs to ensure appropriate data requirements are considered.
  
• Apply GenAI, AI and modern analytical tooling where appropriate to improve productivity and analytical outcomes.
  
• Mentor, guide and upskill less experienced analysts in areas such as SQL, Python, data visualisation and analytical standards.
  
• Participate in knowledge-sharing initiatives, code reviews, interviews and subject matter guidance.
  
• Build strong relationships with stakeholders and manage expectations, requirements and potential conflicts effectively.
  

Key Technical Requirements

• Significant experience in Data Analysis, preferably within banking or financial services.
  
• Advanced proficiency in SQL, including complex queries, query optimisation and working with large datasets.
  
• Strong Python or R skills, including data manipulation and visualisation libraries such as pandas, NumPy, Matplotlib or Seaborn.
  
• Advanced Excel, including macros and VBA.
  
• Strong Power BI, Tableau or similar data visualisation and dashboarding experience.
  
• Advanced statistical analysis and modelling.
  
• Experience with predictive analytics and its application to business/financial data.
  
• Knowledge of data modelling techniques and data structures.
  
• Experience with data quality, validation and analytical controls.
  
• Understanding of risk analysis and its application within financial services.
  
• Knowledge of financial products, services, industry trends, regulations and compliance considerations.
  
• Exposure to AI/GenAI and modern data/analytical tools would be advantageous.
  

Experience & Qualifications

• Proven experience delivering complex data analysis projects and demonstrating business impact through data-driven insights.
  
• Significant experience in data analysis, with financial services/banking experience strongly preferred.
  
• Bachelor's or Honours Degree in Data, Analytical, Technical or a related field.