Data Analyst - Customer Intelligence

Key Responsibilities:

1. Analytics and Insight Generation

• Analyse customer, product usage, commercial, Salesforce, survey and operational data to identify trends, opportunities and areas of risk.
• Support the development of insight that helps the business understand customer behaviour, engagement, retention, product adoption and customer experience.
• Conduct ad hoc analysis to support strategic projects, customer insight initiatives and leadership decision-making.
• Work with Customer Insights colleagues to combine quantitative analysis with customer research findings and create clear recommendations.

2. Data Management and Reporting

• Extract, query, clean and manipulate data from multiple sources using SQL, Python and Excel.
• Support the maintenance and improvement of regular reports, dashboards and insight packs.
• Help define and track customer and business measures, including NPS, customer engagement, retention, product adoption and usage metrics.
• Support data validation and quality checks so reporting and recommendations are based on consistent and reliable data.

3. Data Science, Automation and AI Readiness

• Use Python to automate recurring analysis, reporting processes and data preparation tasks.
• Support statistical analysis, modelling and predictive analytics where appropriate.
• Contribute to proof-of-concept work linked to AI, data science and advanced customer analytics.
• Help identify opportunities to use automation and emerging analytical methods to improve the speed, quality and usefulness of insight.

4. Data Visualisation and Storytelling

• Create clear dashboards and visualisations in Power BI that help teams understand customer and business performance.
• Present analytical findings in a simple, practical way for both technical and non-technical audiences.
• Support the creation of leadership-ready insight summaries, packs and presentations.
• Help translate data into a clear story: what is happening, why it matters and what action should be considered.

5. Collaboration and Business Partnership

• Work cross functionally with key stakeholders, helping to turn business questions into analytical approaches and measurable outputs.
• Share learning openly and contribute to a more joined-up view of customer data and customer evidence.
• Support a culture of evidence-based decision making by helping teams use data with confidence.

Skills and Experience:

Essential

• Bachelor's Degree holder
• Strong analytical and problem-solving skills, with the ability to work with complex datasets and generate practical insight.
• Strong data science and programming skills, with proficiency in Python for data analysis, modelling, automation and statistical applications.
• Experience in data manipulation, querying and analysis using SQL.
• Skilled in data visualisation and presentation of analytical findings using Power BI.
• Competent in Microsoft Excel for data analysis, reporting and business insight generation.
• Ability to communicate analytical findings clearly to business stakeholders.
• Strong attention to detail, especially around data quality, accuracy and interpretation.
• Ability to quickly learn and apply enterprise AI tools and technologies to support technical workflows and business objectives.

Desirable

• Experience using Salesforce and understanding of how CRM data can support analytics and decision-making.
• Understanding of customer insight, market research, customer experience or NPS measurement.
• Working knowledge of cloud computing concepts and cloud-based visual or analytical environments.
• Understanding of data architecture concepts, including data warehousing and data lakes.
• Exposure to cloud computing environments such as Microsoft Azure.
• Exposure to predictive analytics, machine learning, AI-enabled analytics or advanced statistical methods.
• Experience working with customer, commercial, subscription, product usage or behavioural datasets.









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