Hi, I'm Teslim Adeyanju. Financial Data Analyst | ACA. Power BI, Finance & Data Automation.
Financial Data Analyst for FP&A and commercial finance
Microsoft Certified: Power BI Data Analyst Associate (PL-300) and Azure Data Fundamentals (DP-900), ACA Chartered Accountant and Financial Data Analyst — helping organisations turn complex financial data into trusted, decision-ready insight using Power BI, Microsoft Fabric, SQL, Python and Azure data services.
Measurable impact delivered
Career
Develops independent finance-data solutions and portfolio projects using Python, SQL, MySQL, Power BI, and modern data platforms.
Built a self-directed NHS financial analytics project using publicly available data — a normalised MySQL star schema and Python/Pandas ETL pipeline for ~2.1M records across 206 trusts with row-level audit logging — and published fda-toolkit, an open-source Python package with 67 reusable financial-data functions now used by 1,000+ analysts monthly.
Leads financial strategy, budgeting, reserve planning, controls, and trustee reporting, building scenario models and Power BI dashboards for board decisions.
Improved reserve forecasting to flag funding gaps six months ahead, secured £12K in operational-continuity funding, enabled £120K allocation across 8 projects through earlier budget approval, and oversees £1M+ in donor funds with a clean audit record.
Built cost models and rolling forecasts, led monthly reforecast cycles across six departments, and redesigned Power BI reporting on a star-schema model with reusable DAX measures.
Improved forecast accuracy from ±10% to ±8.5% on a £2.3M budget, cut Power BI load times by 35% by removing 120 redundant columns, reduced manual reporting requests by 60% through self-service dashboards, and identified £50K in annual cost savings.
Developed ETL pipelines to consolidate Sage and legacy-system data into Power BI semantic models for sales, procurement, and receivables reporting across 36 states.
Built 55+ Power BI dashboards and 80+ DAX measures, and identified savings opportunities across 85 supplier contracts and 1,200+ SKUs.
Led month-end close, IFRS-compliant financial statements, and board reporting; ran audit-readiness activities and supported capital expenditure tracking. Delivered 60+ board packs on time with a clean 5-year audit record and consistent early delivery.
Managed financial controls, reporting, and intercompany reconciliations across 35 branches, six regional zones, and eight business units. Cut month-end close from 7 days to 3 and eliminated recurring reconciliation errors.
Qualifications
Academic excellence paired with current industry certifications across finance, analytics, and cloud platforms.
University of Hertfordshire, UK · 2022–2024
Top 5% of cohort · HBS Excellence Award 2024 · Student Representative
Grounded in CFA Levels 1 & 2 curriculum, the programme combined quantitative finance, investment analysis, and applied data analytics.
Also holds a Postgraduate Diploma in Finance: University of Lagos, Nigeria, 2017–2018.
Professional Qualifications
Certifications
Technical Stack
The tools I use to turn financial data into insight, and insight into decisions.
Business Intelligence: Power BI (PL-300), DAX, Power Query, Semantic Models, Star Schema
SQL & Databases: SQL, T-SQL, MySQL, Stored Procedures, ETL Pipelines, Data Modelling
Python & Data Engineering: Python, Pandas, NumPy, SQLAlchemy, PyPI Package Development
Finance Systems: Sage 50, Xero (Certified Advisor), QuickBooks, ERP Integration
Microsoft Excel (Advanced): Financial Modelling, Power Query, Pivot Tables, FORECAST.ETS
Cloud & Modern Data Platforms: Azure SQL, Databricks SQL, Azure Databricks, Git
Data Visualisation: Tableau, Dashboard Design, Interactive Reporting
AI & Automation: Azure OpenAI, Prompt Engineering, Retrieval Augmented Generation (RAG), Claude API
Portfolio
Finance-focused case studies spanning classical analytics, Power BI, and modern AI.
67 functions · 8 modules · reusable financial-data workflow
Python framework for automating financial data cleaning, validation, transformation, and audit logging. Eliminates manual reconciliation, broken schemas, and audit gaps—so analysts focus on insight, not data repair.
206 NHS trusts across 3 financial years · Python-to-MySQL ETL pipeline
Engineered end-to-end Python ETL pipeline ingesting NHS England financial data into MySQL star schema with analytical views, KPI metrics, and Power BI integration across 206 trusts.
Management Accounting · Forecasting · Variance Analysis
Designed forecasting models and variance analysis framework using Python — translating core management accounting skills into data-driven analytics with professional visualisations.
GOOGL · AMZN · AAPL · MSFT · Monte Carlo Simulation
Full portfolio risk analysis framework: daily returns, volatility computation, Sharpe ratio calculation, and 30-year Monte Carlo simulation for informed investment risk modelling.
CTEs · Window Functions · Data Quality Analysis
Advanced SQL analytics using CTEs, window functions, aggregations, and data quality frameworks — applied to student wellbeing analytics in Jupyter and MySQL.
29 DAX Measures · 5 KPI Domains · Enterprise Dashboard
Advanced Power BI model with 29 complex DAX measures tracking profitability, growth, efficiency, pricing, and risk metrics. Interactive dashboards with drill-through capabilities for business intelligence.
10-agent architecture · 21+ financial metrics · validated on Apple, Amazon & Colgate annual reports
Multi-agent AI platform that extracts and interprets financial statements — automated metrics and ratio calculation, evidence-linked risk and anomaly detection, and AI-generated executive commentary, with Python handling every calculation so results stay auditable.
1,299 indexed sections · 5 HMRC internal manuals · source-linked answers
Retrieval-augmented Q&A system that grounds UK tax answers in official HMRC internal manuals instead of an LLM's memory — every response traces back to the exact GOV.UK source page, or the system declines to answer.
| # | Project | Focus | Stack | |
|---|---|---|---|---|
| 02 | Financial Data Pipeline | ETL · Forecasting · Trading | Python | ↗ |
| 05 | UK Mutual Fund Performance | Fund Analysis · Performance | — | ↗ |
| 06 | ML Financial Analysis | Regression · Classification · Ensemble Models | Python | ↗ |
| 07 | NHS Waiting List Analytics | Healthcare · Trend Analysis | Python | ↗ |
| 08 | Diamond Price Prediction | EDA · Feature Engineering · ML | Python | ↗ |
| 09 | Superstore Sales Prediction | Retail · Forecasting · ML | Python | ↗ |
| 10 | Retail Marketing Prediction | Marketing · Consumer Behaviour | Python | ↗ |
| 11 | Salary Prediction (SHAP) | ML · Explainability · SHAP | Python | ↗ |
| 12 | Lead Conversion Model | Marketing · Classification | Python | ↗ |
| 13 | YouTube Sentiment Analysis | NLP · Sentiment · Text | Python | ↗ |
| 14 | UK Immigration Impact Analysis | Power BI · Geographic Data · Policy | Power BI | ↗ |
| 15 | World University Ranking | EDA · Data Analysis | Python | ↗ |
| 16 | AI Career Coach | AI Agent · LLM | HTML/JS | ↗ |
| 17 | AI News Automator | AI · Streamlit · Automation | Python | ↗ |
| 18 | Email Agent | AI Agent · Automation | Python | ↗ |
| 19 | Ollama Local Agent | Local LLM · AI | Shell | ↗ |
| 21 | MySQL Fundamentals to Advanced | Core SQL to Analytics · Python Integration | MySQL + Python | ↗ |
Some links go to my second GitHub account, github.com/UthmanAdeyanju (Uthman is my other given name).
Get In Touch
Interested in discussing Finance Analytics, Data Engineering, Power BI implementation, or Python-based financial solutions? I'm based in the UK and available for immediate engagement.
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