Kenya
Where are we losing money—and why haven’t we seen it? Most business problems don’t look like problems at first. They look like: • Stable revenue • “Decent” performance • Decisions that feel right But underneath that… money is being lost quietly. Not in obvious ways. In pricing that was set once and never revisited. In operations that seem efficient—but aren’t. In customers that look valuable—but don’t drive profit. This is what makes it dangerous: 👉 The business is running 👉 The numbers look fine 👉 But the losses are hidden in patterns no one is questioning And over time, that becomes expensive. I work with decision-makers to remove guesswork when the stakes are high. Because at that level: • A small inefficiency compounds into significant loss • A wrong assumption delays growth • A blind spot quietly drains revenue My role is simple: 👉 Identify where money is being lost 👉 Expose the patterns behind it 👉 Turn that into clear, confident decisions No unnecessary complexity. No dashboards that don’t get used. Just clarity on what’s working, what’s not— and where the real opportunity is. I think of this as the Decision Layer— where the quality of decisions directly impacts profit, risk, and growth. If you’re responsible for revenue, performance, or strategy, there’s a high chance something important is being missed. Let’s connect.
As a freelance machine learning specialist, I’ve had the privilege of working with diverse clients across e-commerce, healthcare, and finance. My focus has been on creating predictive models and real-time dashboards that drive decision-making and improve operational efficiency. Remit: • Deploying a classification model for a major e-commerce client, which improved the accuracy of user purchase predictions across 10,000+ transactions. • Fine-tuning deep learning algorithms in the healthcare space, reducing model error rates and improving diagnostics accuracy. • Building predictive models for finance, processing over 200,000 rows of transaction data to identify risk indicators and enhance reporting precision.
Working independently as a Data Specialist has allowed me to develop and deploy data-driven solutions that support business growth. Remit: • Automated data pipelines using Python to enable real-time monitoring of customer churn across 100,000+ records. • Developed Tableau dashboards to track logistics operations and streamline reporting for 12,000+ orders. • Cleaned and normalized complex agricultural datasets with over 500 variables, making them compatible across multiple analytics platforms.