Victoria Abel

Data Analyst with a background in Medical Laboratory Science, specializing in the intersection of clinical diagnostics and statistical analysis. Proficient in SQL, Excel, and Power BI, with a proven ability to manage the full data lifecycle—from collection and cleaning to visualization and insight generation. Experienced in handling high-integrity medical data and translating complex technical findings into actionable business or clinical strategies.

• CORE DATA PROJECT
• Business Operations & Revenue Dashboard | Excel & Power BI
• Developed a comprehensive financial tracking system for a service-based business, consolidating data from multiple sources to track monthly revenue and expenses.
• Designed an automated Power BI dashboard to visualize client acquisition costs and service profit margins, identifying a 12% revenue leak in underperforming service lines.
• Utilized Excel Power Query to automate weekly financial reports, reducing manual data entry time by 5 hours per week.
• Customer Segmentation & Sentiment Analysis | SQL & Python
• Queried a multi-table database using SQL to segment customers based on purchasing frequency and lifetime value (RFM Analysis).
• Cleaned and pre-processed 10,000+ rows of unstructured customer feedback data using Python, performing sentiment analysis to identify key pain points.
• Presented data-driven recommendations that led to a targeted marketing campaign, increasing client retention by 15%.
• Global Sales Performance Analysis | SQL & Tableau
• Wrote complex SQL scripts to extract and aggregate sales data across different geographical regions.
• Identified seasonal trends and product outliers by performing Exploratory Data Analysis (EDA).
• Created interactive Tableau visualizations to communicate quarterly growth metrics to non-technical stakeholders
• PROFESSIONAL EXPERIENCE
• Research & Clinical Analyst (University of Calabar Teaching Hospital )
• Managed high-integrity datasets for a research project involving FBC profiles, ensuring 100% data accuracy and compliance with ethical standards.
• Performed statistical significance testing (T-tests/ANOVA) to validate research hypotheses.
• Translated technical lab findings into clear, structured abstracts and reports for academic review.