Data Analyst CV Example

Lead data analyst responsible for customer analytics and business intelligence across multiple product teams, supporting data-driven decision making for a user base of 7+ million customers.

• Built and maintained 12 automated Tableau dashboards tracking KPIs across 3 business units, reducing manual reporting time by 20 hours per week and improving data refresh frequency from weekly to daily
• Conducted comprehensive customer segmentation analysis using Python and scikit-learn on 2.5 million customer records, identifying 4 high-value cohorts that informed a targeted retention campaign resulting in 23% reduction in churn
• Designed and implemented robust A/B testing framework for marketing team using statistical significance testing, leading to 15% improvement in email conversion rates and £180k additional monthly revenue
• Developed predictive models using Python and XGBoost to forecast weekly order volumes with 92% accuracy, enabling optimised driver allocation and reducing delivery times by 8%
• Collaborated with product managers to analyse user journey data, identifying 3 critical drop-off points that led to UX improvements increasing conversion rates by 12%
• Created automated anomaly detection system using SQL and Python, reducing time to identify data quality issues from 2 days to 2 hours
• Presented monthly performance insights to C-suite executives, translating complex analytical findings into strategic recommendations that influenced £2.3m budget allocation decisions

Supporting senior analysts and audit teams with data extraction, analysis and reporting across financial services and technology clients, handling datasets containing up to 10 million records.

• Wrote and optimised complex SQL queries across 15+ database tables to extract and clean financial data for audit engagements, improving query performance by 40% through effective indexing strategies
• Created 8 monthly performance dashboards for 3 partner teams using Power BI, tracking audit progress metrics and client satisfaction scores with automated refresh capabilities
• Automated data validation checks using Python pandas and numpy, reducing manual QA time by 60% and eliminating 95% of human errors in financial reconciliation processes
• Performed statistical sampling analysis on client transactions totalling £50m+, ensuring audit compliance and identifying 12 instances of potential revenue recognition issues
• Developed ETL pipelines using Python and SQL to standardise data from 20+ client systems, reducing data preparation time from 3 days to 6 hours per engagement
• Conducted variance analysis on financial statements, identifying discrepancies that led to recovery of £340k in client adjustments across 5 major audit engagements
• Mentored 2 graduate trainees in SQL and Excel techniques, improving team productivity by 25% and reducing training time from 4 weeks to 2 weeks

Summer internship within the Risk Analytics team, supporting credit risk modelling and regulatory reporting for the UK retail banking division.

• Assisted in developing credit scoring models using logistic regression in Python, contributing to model validation that covered £2.8bn loan portfolio
• Created data visualisations in Tableau to present model performance metrics to senior stakeholders, improving model interpretability and regulatory compliance
• Performed data quality assessment on customer credit data, identifying and documenting 15 data consistency issues that improved model accuracy by 3%
• Supported monthly regulatory reporting process by automating data extraction procedures, reducing preparation time by 8 hours per month
• Conducted exploratory data analysis on transaction patterns, contributing insights that informed the development of fraud detection algorithms