Sharjeel Asif

Data Analyst with 4+ years of experience producing KPI dashboards, management reporting and commercial analysis that support operational and strategic decision-making. Skilled in Power BI, SQL and Excel, with a track record analysing sales performance, margins and variances to identify performance drivers and support forecasting. Strong cross-functional communicator, partnering with Operations, Finance and senior stakeholders, with analytical work contributing to £1.9M+ in measurable impact.

Data Analyst - Great Ormond Street Hospital Charity

(2025-12)

• Built Power BI KPI dashboards and executive-level reporting across 350K+ CRM and operational records, supporting £3.6M revenue for senior stakeholders.
• Analysed performance trends in customer and campaign data using SQL and Python, identifying drivers that supported £500K fundraising growth.
• Used SQL and DAX to validate and segment large datasets, improving reporting accuracy and lifting response rates by 25%, contributing £200K donations.

BI Reporting Analyst / Department Lead - Primark

(2024-03 - 2025-12)

• Analysed sales performance, margins and variances across large commercial and operational datasets using SQL, Excel and Power BI, contributing to £1.2M revenue improvement.
• Partnered with operational and senior stakeholders across departments to standardise KPIs and management reporting, improving decision-making by 40%.
• Implemented a new stock allocation strategy improving operational efficiency and demand-driven replenishment, reducing stockouts by 30%.

Insight & Reporting Analyst - Public Sector Insights Program

(2020-04 - 2023-04)

• Developed SQL Server and Power BI KPI reporting across 15+ complex datasets, supporting business process improvement and reducing recurring analysis delivery time by 45%.
• Presented performance trends and evidence-based insight to technical and non-technical stakeholders, supporting decisions affecting 500K+ users.
• Built automated validation frameworks and data governance controls, improving data accuracy by 32% and reducing reporting errors by 28%.

MSc - Data Science - University of Essex

BS - Electrical Engineering - National University of Science & Technology