About
Data-inclined commerce graduate with a foundation in accounting, financial analysis, and information technology. Trained in Excel-based data handling, structured financial datasets, Bloomberg finance fundamentals, and emerging AI concepts. Demonstrates strong analytical discipline, structured thinking, and curiosity-driven learning. Currently pursuing advanced studies in Data Science, with an interest in entry-level data analysis, business analytics, and data-supported finance roles.
Skills
Data Analysis & Tools
- Microsoft Excel (data cleaning, sorting, filtering, formulas, reporting)
- Microsoft Access (basic database concepts, storage, retrieval, validation)
Finance as a Data Domain
- Financial statements fundamentals
- Accounting records as structured datasets
- Introductory financial and managerial analysis
Programming / Web Foundations
- HTML (basic structure)
- CSS (basic layouts)
AI & Emerging Technologies
- Generative AI (foundational understanding)
- Prompt engineering for summarization, ideation, and analytical support
- Awareness of machine learning and NLP workflows
Education
PGDM – Data Science
International Institute of Business Studies
2025–2027 (Pursuing)
Bachelor of Commerce (Accounting)
North East Christian University
2021–2024
Certifications
Bloomberg Finance Fundamentals
Bloomberg | November 2025
Generative AI Mastermind
Outskill | November 2025
Financial Accounting – Certificate of Merit
CTLC | August 2024
Tally Prime & MS Access
O level Certification in Computer Application
NIELIT | January 2025
Projects
Aurelius Strategic Holdings - Financial Command Centre
Feb 2025
Problem: Executive teams needed board-ready financial insights from quarterly statements, but manual dashboard creation required hours of work and lacked real-time interactivity. Traditional reporting methods couldn't provide instant quarter-over-quarter comparisons or dynamic KPI updates.
Approach: Designed a normalized data architecture with vertical quarterly tables for Income Statements and Balance Sheets. Built an automated KPI engine using INDEX/MATCH formulas to calculate 8 key metrics (liquidity, profitability, solvency, growth ratios). Implemented dynamic quarter selection with cascading formula updates across all calculations. Created four integrated visualizations (line charts, clustered columns, stacked bars, radar charts) linked to live data. Developed VBA macros for one-click PDF export with professional formatting.
Outcome: Delivered a fully automated dashboard that updates all metrics, charts, and executive insights instantly upon quarter selection. Eliminated manual calculation errors through comprehensive IFERROR handling. Achieved zero formula errors across 54+ calculations. Created board-ready presentation materials exportable to PDF with consistent Corporate Elite branding. Reduced quarterly reporting preparation time from hours to minutes while improving data accuracy and visual clarity.
Skills: Microsoft Excel · Advanced Excel Formulas (INDEX/MATCH) · Data Validation · Financial Ratio Analysis · Dashboard Design · VBA Macros · Data Visualization · Error Handling · Financial Modeling
View on GitHubLUMINA: Personal Capital Intelligence & MIS Engine
Problem: Traditional personal finance tracking lacks the analytical depth and executive-level intelligence required for strategic capital allocation decisions. Needed a sophisticated, data-driven system to transform raw financial transactions into actionable insights with predictive capabilities and automated reporting.
Tools: Microsoft Access (relational database), Microsoft Excel (dashboard & analytics), VBA (automation), SQL (data extraction), AI/LLMs (narrative insights generation)
Approach: Architected a hybrid dual-tier system with MS Access as the normalized relational backend (3NF schema) containing four core tables (Transactions, Categories, Payment Methods, Income Sources) with enforced referential integrity. Designed complex SQL queries for multi-dimensional aggregation and ETL processes. Built an Excel-based MIS frontend featuring 10+ advanced formulas (LET, FILTER, XLOOKUP, SUMIFS) to calculate dynamic KPIs including net cash flow, savings rate, liquidity runway, debt servicing ratio, and CAGR. Developed VBA macros for automated data refresh via ADO connectivity and PDF report generation. Implemented the "Aurelius" visual standard with professional Deep Slate & Emerald color palette across 8+ interactive charts (donut, waterfall, radar, heatmap). Integrated AI by structuring financial data summaries into LLM prompts, generating executive-level narrative insights with trend identification and actionable recommendations.
Outcome: Demonstrated enterprise-grade technical competencies in relational database design, SQL optimization, advanced Excel modeling, VBA programming, ETL architecture, and AI integration. Developed proficiency in financial analysis frameworks including variance analysis, ratio calculations, and forecasting. Created production-ready business intelligence system showcasing end-to-end data pipeline development from persistence layer through analytical visualization to AI-augmented decision support.
Skills: Microsoft Access · Relational Database Design · SQL · Microsoft Excel · Advanced Formulas (LET, FILTER, XLOOKUP, SUMIFS) · VBA Macros · ETL Architecture · Financial Analysis · Dashboard Design · AI Integration · Data Visualization · 3NF Schema Design
View on GitHubVANGUARD: Retail Intelligence & Revenue Attribution Engine
Problem: Fragmented, high-volume retail transaction logs lacked structure, consistency, and analytical depth—limiting the organization's ability to optimize revenue, predict churn, and make data-driven strategic decisions.
Tools: Microsoft Excel (Power Query, Advanced Formulas, Dynamic Arrays), Microsoft Access (Relational Database Design), SQL (CTEs, Window Functions, Advanced Queries), VBA (Workflow Automation & Reporting), AI Tools (Insight Generation & Strategic Analysis)
Approach: Designed a normalized relational database schema in Microsoft Access (Customers, Products, Transactions) implementing referential integrity, indexed keys, and standardized data types for scalable analytics. Built a multi-stage ETL pipeline using Power Query to cleanse raw datasets through null-value imputation, deduplication, type harmonization, and statistical outlier detection, achieving 99.9% data integrity. Developed 10 advanced KPI models in Excel using dynamic arrays and statistical functions, including Customer Lifetime Value (CLV), Revenue Velocity, Price Elasticity, Category Concentration, and Inventory Turnover Ratio to enable comprehensive performance tracking. Created 14 complex SQL queries leveraging CTEs, window functions, joins, and aggregations to conduct RFM-based segmentation, cohort analysis, churn risk identification, and seasonal revenue forecasting. Automated reporting workflows with 10 VBA macros for data refresh, PDF export, executive email generation, and automated validation checks—reducing manual effort by approximately 60%. Applied AI-assisted prompting frameworks to surface strategic insights, identifying $340K in growth opportunities, $180K in churn exposure, and $250K in operational inefficiencies. Designed an executive dashboard featuring treemaps, time-series decomposition charts, bubble visualizations, and regional heatmaps to translate technical metrics into board-level strategic narratives.
Outcome: Delivered an end-to-end production-grade analytics system transforming raw transactional data into actionable revenue intelligence. Quantified high-impact strategic opportunities exceeding $770K in potential financial optimization. Strengthened expertise in data normalization, advanced Excel modeling, SQL optimization, predictive analytics, and business intelligence storytelling. Demonstrated ability to bridge technical analytics with executive decision-making through automated reporting and strategic insight generation.
Skills: Microsoft Excel · Power Query · Dynamic Arrays · Microsoft Access · SQL · CTEs · Window Functions · RFM Segmentation · Cohort Analysis · VBA Macros · ETL Pipeline · Data Normalization · Advanced KPI Modeling · Dashboard Design · Data Visualization · AI-Assisted Analysis
View on GitHubResume
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