Data & BI Analyst with 7+ years of commercial experience delivering SQL, Python and Power BI solutions that improve operational efficiency, marketing performance and business visibility.
I design structured KPI architectures, automate reporting pipelines and build analytical systems that support measurable decision making.
- Reduced reporting cycle time by 50 percent through Python and SQL ETL automation
- Improved operational efficiency by 40 percent via redesigned KPI dashboards across 30+ Power BI reports
- Increased campaign response rates by 40 percent using churn prediction and RFM segmentation
- Improved reporting reliability to 99 percent through structured data validation controls
- Built scalable performance tracking systems supporting growth from 5 to 80+ staff
Over seven years at Quick Choice, I progressed from Customer Service to Marketing Analytics and Operations Analytics. This cross-functional experience built strong commercial judgement alongside technical depth.
I completed an MSc in Data Analytics in 2024, strengthening capability in machine learning, large-scale data processing and statistical modelling.
End-to-end modelling project using 22,000+ UK public collision records to identify environmental and behavioural severity drivers.
- Engineered structured dataset from raw public records
- Applied Logistic Regression, Random Forest and Gradient Boosting models
- Achieved 97 percent classification accuracy
- Translated outputs into interactive Power BI dashboards
Multi-year benchmark analysis comparing EHCP attainment against national averages.
- Identified sustained 11 percent attainment gap
- Highlighted data quality inconsistencies
- Structured outputs for strategic intervention planning
Longitudinal benchmarking of renewable installations growth and regional contribution to UK generation.
- Analysed 10-year growth trajectory
- Benchmarked regional share against national totals
- Designed reusable monitoring framework
Distributed processing of 10+ years of UK police crime data using PySpark.
- Built scalable transformation workflows
- Identified geographic concentration hotspots
- Structured outputs for planning and resource allocation insight
Interactive executive dashboard for revenue and operational performance monitoring.
- Designed structured KPI framework
- Built Power Query data transformation layer
- Delivered leadership-ready reporting
Predictive modelling and segmentation project focused on retention and campaign optimisation.
- Built churn prediction models
- Designed RFM segmentation framework
- Improved response rates by 40 percent
SQL • Python • Power BI • Excel • PySpark • BigQuery • GA4
Predictive modelling • KPI design • Data validation • A/B testing • Geospatial analysis
Currently developing Azure Data Engineering capability through structured hands-on projects.