I translate complex datasets into strategic decisions that move the needle, from churn models with 86% accuracy to supply chain automation that saves 50% in processing time. I work across the public sector, financial services, e-commerce, and startups at the intersection of analysis, machine learning, and commercial impact.
About me
I started my career building predictive models and extracting data insights for a digital networks company in Lagos, and quickly learned that the hardest part of analytics is not the model. It is earning the trust of a director with competing priorities and getting them to act on what the data is saying.
Over eight years, I have led analytics projects across public sector waste management, real estate, financial services, and early-stage startups. My work has directly influenced operational efficiency, cost reduction, funding strategy, and machine learning deployments, always with a focus on the decision at the end of the data, not the data itself.
I hold an MSc in Data Science from the University of Salford and am currently based in Manchester. I am open to senior analyst, lead analyst, and data science roles where I can continue building high-impact analytical capability.
Selected work
Led end-to-end churn analysis for a 10K+ customer credit card issuing project, identifying that 45% of selected customers are awarded the wrong credit cards, which is at-risk of accounts shared, and three early behavioural signals invisible to the sales team. Partnered with customer support and operations teams to redesign the intervention, shifting from reactive to predictive outreach 45 days before renewal.
Designed this transactional analysis, which contains all the purchases occurring between, integrating lead-time variance, customer shopping and inventory, buffering into a single operation. where the model monitors the purchase of goods in wholesale and services rendered online, quantifying patronage frequency.
Inflation, import and export of goods, gross capital creation, industry, manufacturing industries, and other elements that impact economic labour in the listed countries are included in the statistics.
Built an anomaly detection pipeline processing 2M+ daily transactions to surface high-risk behavioural clusters that existing rule-based filters consistently missed. Worked directly with the Chief Risk Officer and external auditors to ensure the model met regulatory documentation standards before production deployment.
I led an end‑to‑end analysis of a large‑scale hospitality review dataset (53,647 customer reviews across hotels and restaurants in Thailand and surrounding regions). The dataset included five structured fields—ID, review date, location, establishment name, and full review text—each containing unique customer insights.
Seniority signals
For recruiters
Data Scientist and Analyst with 8 years of experience spanning public sector operations, real estate, financial services, and early-stage startups. Specialises in turning complex datasets into decisions that drive revenue, reduce cost, and improve operational performance. Proficient across the full analytics stack from SQL and Python modelling through to Power BI and Tableau dashboards presented directly to executive stakeholders. Holds an MSc in Data Science from the University of Salford.
Delivered staff training on new and existing systems at Lancashire County Council resulting in a 70 percent KPI improvement across the team. Identified continuous improvement opportunities that increased operational work rate and turnaround time by 20 percent. Architected a vendor scoring algorithm at Marketbuddyng that was adopted into the product roadmap, and supported a 500,000 USD seed fundraise with financial modelling presented directly to the executive team.
Get in touch
I am open to senior analyst, lead analyst, and data science roles, full-time or contract. I work best with teams that care about the quality of decisions, not just the quantity of dashboards.