Builder. Data Scientist.
Finance Expert.
I build production AI applications using agentic AI. My background is in finance (FCCA) and data science (MSc with Distinction) — which means I understand what it takes to turn a messy real-world problem into a working product.
ACCA Fellow
FCCA
MBA Finance
Wisconsin IUC
MSc Data Science
Distinction · 2025
BSc Accounting
First Class
2025
MSc Data Science — Distinction
Middlesex University London
Top 5 Best Project Award
Machine Learning · Big Data Analytics · NLP · Cloud Systems · AI Ethics
Dissertation: Food Insecurity Early Warning System — Two-stage cascade ML across 18 African nations
MBA
MBA Finance
Wisconsin International University College, Ghana
Strategic analysis · Quantitative methods · Data-driven decision making
FCCA
Fellow Chartered Certified Accountant
Association of Chartered Certified Accountants
BSc
BSc Administration (Accounting) — First Class
University of Ghana Business School
Statistical analysis · Research methodology · Quantitative analysis
Certs
MATLAB Programming & Analytics (MathWorks 2025) · Microsoft Power BI Expert · Advanced Excel & VBA Specialist · Python for Data Science
2023–2024
Finance Manager — Analytics & Automation
SIA QSR Ltd
Architected integrated analytics platform using Python and Power BI, improving executive decision-making speed by 35%. Developed predictive financial models achieving 20% improvement in resource allocation accuracy. Built automated reporting systems reducing manual processing time by 40%.
Python · Power BI · Predictive Modeling · Process Automation
2020–2023
Finance Manager — Business Intelligence & Predictive Analytics
Chase Petroleum Company Limited
Spearheaded enterprise-wide BI transformation, reducing manual reporting by 50% and delivering interactive dashboards for $50M+ annual revenue operations. Designed statistical forecasting models improving budget accuracy by 15%.
BI Transformation · Time Series Analysis · ETL Pipelines · $50M+ Operations
2009–2020
Progressive Leadership — Oil & Gas Analytics
Puma Energy · Juwel Energy · Cardinal Petroleum
Led analytical operations across multiple subsidiaries, managing $300M+ treasury operations. Achieved zero audit discrepancies and 100% reporting accuracy. Improved profit margin visibility by 25% and working capital efficiency by 18% through predictive modeling.
Treasury Analytics · Risk Modeling · Financial Modeling · Team Leadership
Machine Learning & AI
Supervised & Unsupervised Learning (Classification, Regression, Clustering) · Deep Learning (TensorFlow, Keras, PyTorch) · NLP & Sentiment Analysis (BERT, Transformers) · Computer Vision (CNN, Image Classification) · Time Series Forecasting (ARIMA, LSTM) · MLOps & Model Deployment (Production Pipelines, Monitoring) · Explainable AI (SHAP, LIME, Feature Importance)
AI & LLM Development
LLM APIs — agentic patterns, tool use, function calling · Multi-Agent Systems — orchestration, handoffs, error recovery · Production LLM Apps — deployed across finance, education, wellness · Agentic Developer Platform — API provisioning and integration
Financial Analytics
Financial Modeling & Forecasting · Risk Analysis & Management · Business Intelligence & Reporting · Strategic Planning & Decision Support · Accounting Systems & Process Optimization · Regulatory Compliance & Audit Analytics (IFRS, SOX)
Technical Stack
Languages: Python, R, SQL, VBA, MATLAB · ML/DL: scikit-learn, TensorFlow, Keras, PyTorch, XGBoost · Data: Pandas, NumPy, PySpark, SQL Server, PostgreSQL · Viz: Power BI, Tableau, Matplotlib, Seaborn, Plotly · Tools: Git, Docker, Streamlit, Flask, FastAPI · Cloud: AWS (SageMaker, S3, EC2), Azure ML, GCP
Domain Expertise
Financial Services: Fraud Detection, Risk Modeling, Credit Scoring · Healthcare: Medical Image Classification, Disease Prediction · Retail: Demand Forecasting, Customer Analytics, Market Basket Analysis · Oil & Gas: Energy Trading & Pricing, Operations Optimization
Builder-Practitioner: I don't just build ML models — I ship full AI-powered applications using agentic AI. From agentic ERPs to AI tutors, I've gone from concept to production across multiple domains, combining deep finance expertise (FCCA) with hands-on AI development.
Full-Stack ML Expertise: From deep learning (PyTorch, TensorFlow) to gradient boosting (XGBoost, LightGBM, CatBoost) to NLP transformers (BERT, GPT) — I select and implement the right technique for each business problem, not just the trendiest algorithm.
Multi-Domain Versatility: Proven success across Finance (fraud detection, stock forecasting), Healthcare (medical imaging, disease prediction), Retail (demand forecasting, customer analytics), NLP (sentiment analysis, NER), and Computer Vision (object detection, image classification).
Production-First Mindset: Every project includes interactive Streamlit dashboards, FastAPI endpoints, Docker deployment, and comprehensive documentation. I build systems that stakeholders can actually use — not just notebooks that collect dust.
Proven Impact: 18+ production ML projects with metrics like 99.78% R², 98% ROC-AUC, $131K+ savings per 100K transactions, and consistent delivery of measurable business outcomes across diverse industries.