About Me

I'm a Data Scientist & ML Engineer with 15+ years of analytical leadership, uniquely positioned at the intersection of advanced machine learning and financial expertise.

ACCA Fellow
MBA Finance
MSc Data Science (2026)
BSc Accounting (First Class)

Professional Summary

With a rare combination of Chartered Accountancy (FCCA) and Advanced Machine Learning expertise, I architect production-grade ML systems that deliver measurable, transformative business impact. My 15+ years leading financial analytics and enterprise intelligence initiatives uniquely position me to bridge the gap between cutting-edge AI and real-world business value.

I specialize in transforming complex business challenges into scalable, production-ready ML solutions across Finance & Risk Analytics, Healthcare AI, Retail Intelligence, and Enterprise Automation — delivering end-to-end ML pipelines from strategic concept to deployed, monitored production systems.

Proven Track Record: 17+ production ML projects deployed, consistently achieving 90%+ model accuracy, driving millions in cost savings, and enabling data-driven decision-making at the executive level.

Education & Certifications

In Progress

MSc Data Science

Middlesex University, London

Expected: January 2026

Machine Learning, Big Data Analytics, NLP, Cloud Systems, AI Ethics

Completed

MBA Finance

Wisconsin International University College, Ghana

Strategic analysis, quantitative methods, data-driven decision making

Fellow

FCCA (Fellow Chartered Certified Accountant)

Association of Chartered Certified Accountants

Professional Qualification

First Class

BSc Administration (Accounting)

University of Ghana Business School

First Class Honours

Statistical analysis, research methodology, quantitative analysis

Professional Certifications

MATLAB Programming & Analytics (MathWorks 2025)
Microsoft Power BI Expert
Advanced Excel & VBA Specialist
Python for Data Science

Professional Experience

Senior Finance Manager (Advanced Analytics & Automation)

SIA QSR Ltd

Jul 2023 - Dec 2024

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

Finance Manager (Business Intelligence & Predictive Analytics)

Chase Petroleum Company Limited

Jul 2020 - Jun 2023

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

Progressive Leadership in Oil & Gas Analytics

Puma Energy (2017-2020) | Juwel Energy (2013-2016) | Cardinal Petroleum (2009-2013)

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

Core Competencies

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)

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

What Sets Me Apart

Rare Dual Expertise: A unique combination of FCCA Chartered Accountancy, 15+ years business leadership, and cutting-edge ML/AI capabilities. I don't just build models — I understand the business context, ROI implications, and strategic value that makes them impactful.

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, insurance pricing), 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.

Explainable AI Champion: SHAP, LIME, Grad-CAM, and feature importance analysis in every project. I believe ML models must be interpretable for business adoption, regulatory compliance, and building stakeholder trust.

Proven Impact: 17+ 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.