Data analyst with seven years in retail and subscription businesses, working mainly in SQL, Python and Power BI. Known for turning messy operational data into analysis that changes a decision. Looking for a senior analyst role with more ownership of experimentation.
Work experience
Data Analyst, Fernbrook Subscriptions Ltd
Leeds | Apr 2022 – Present
Built a churn-risk model in Python that the retention team used to target 4,000 customers a month, reducing monthly churn from 5.1% to 3.3%
Designed the company's A/B testing framework and analysed 22 pricing and onboarding experiments in the first year
Rebuilt 14 Power BI reports on a single tested data model, cutting report refresh failures from weekly to fewer than one a quarter
Analysed delivery-slot demand, informing a courier contract change that saved an estimated £180,000 a year
Ran monthly SQL workshops for 12 colleagues in finance and marketing
Junior Data Analyst, Calder Home Retail
Wakefield | Sep 2019 – Mar 2022
Automated the weekly trading report with SQL and Python, saving the commercial team 6 hours each Monday
Mapped stock-outs across 48 stores, identifying 3 replenishment rules behind 40% of lost sales
Cleaned and merged loyalty-card data for 1.2 million customers ahead of a CRM migration
Presented quarterly basket analysis to the buying director and 8 category managers
Education
BSc Economics with Placement Year, University of Pennine Vale
Huddersfield | 2015 – 2019
First-class honours; dissertation on regional house price modelling in R
Completed a 12-month placement at Moorside Research, analysing 6 consumer surveys of up to 3,000 respondents in SPSS and Excel
Data analyst with seven years in retail and subscription businesses, working mainly in SQL, Python and Power BI. Known for turning messy operational data into analysis that changes a decision. Looking for a senior analyst role with more ownership of experimentation.
Work experience
Data Analyst, Fernbrook Subscriptions Ltd
Leeds | Apr 2022 – Present
Built a churn-risk model in Python that the retention team used to target 4,000 customers a month, reducing monthly churn from 5.1% to 3.3%
Designed the company's A/B testing framework and analysed 22 pricing and onboarding experiments in the first year
Rebuilt 14 Power BI reports on a single tested data model, cutting report refresh failures from weekly to fewer than one a quarter
Analysed delivery-slot demand, informing a courier contract change that saved an estimated £180,000 a year
Ran monthly SQL workshops for 12 colleagues in finance and marketing
Junior Data Analyst, Calder Home Retail
Wakefield | Sep 2019 – Mar 2022
Automated the weekly trading report with SQL and Python, saving the commercial team 6 hours each Monday
Mapped stock-outs across 48 stores, identifying 3 replenishment rules behind 40% of lost sales
Cleaned and merged loyalty-card data for 1.2 million customers ahead of a CRM migration
Presented quarterly basket analysis to the buying director and 8 category managers
Education
BSc Economics with Placement Year, University of Pennine Vale
Huddersfield | 2015 – 2019
First-class honours; dissertation on regional house price modelling in R
Completed a 12-month placement at Moorside Research, analysing 6 consumer surveys of up to 3,000 respondents in SPSS and Excel
Visualisation: Power BI (DAX), Looker Studio, matplotlib
Methods: A/B testing, regression, cohort and churn analysis, forecasting
Ways of working: Git, dbt, documentation, presenting to non-technical audiences
Certifications
Microsoft Certified: Power BI Data Analyst Associate, Microsoft, 2022
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Applicant tracking systems
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