Turning raw business data into decisions that move the needle.
I work across the full analytics stack - from writing production SQL against audited financial data to building executive Power BI dashboards that non-technical stakeholders actually navigate themselves. My projects are built on real business problems: revenue segmentation, customer cohort decay, logistics failure rates, IFRS-adjusted financial trends. Not Kaggle demos.
Based in Nairobi. Open to remote international analyst roles and Nairobi-based positions.
Analytics engineering I write clean, documented SQL — window functions, CTEs, subqueries, performance tuning. My Safaricom analysis pulled directly from EY-audited annual reports (FY2015–FY2025) and applied IFRS 15, IFRS 16, and IAS 29 hyperinflation adjustments before a single query ran. That is the standard I hold myself to.
Business intelligence I build Power BI dashboards with proper data models, 20+ DAX measures, and bookmark navigation — designed for executives who need answers in under 30 seconds. My Olist dashboard connects live to PostgreSQL 17. My Safaricom dashboard handles a decade of multi-segment financial data with consistent KPI logic across every page.
Financial and economic analysis BSc Economics and Finance. I understand what P&L, variance analysis, revenue mix, and margin compression actually mean for a business — not just how to calculate them. I've done financial reporting and reconciliation in logistics (Flekc Freight) and revenue analysis in hospitality (Truce Lounge).
Field data and research Collected and managed structured field data on UNICEF and ILO projects using KoboToolbox and ODK. I know the difference between data that looks clean and data that actually is.
| Domain | Tools and capabilities |
|---|---|
| SQL | PostgreSQL 17, window functions, CTEs, cohort queries, performance optimisation |
| Business Intelligence | Power BI, DAX, data modelling, KPI design, bookmark navigation |
| Spreadsheet analytics | Excel — PivotTables, Power Query, financial models, KPI dashboards |
| Data storytelling | Translating analysis into clear business recommendations |
| Financial analysis | Variance analysis, revenue segmentation, IFRS treatment, reconciliation |
| Field research | KoboToolbox, ODK, stakeholder engagement, structured data collection |
| Automation | n8n workflow automation, API integrations |
| Web | HTML, CSS, JavaScript — functional, not decorative |
| In progress | Python (Pandas, Matplotlib), Microsoft PL-300 |
| Project | Stack | What it does |
|---|---|---|
| Safaricom Financial Analysis | PostgreSQL 17 | FY2015–2025 analysis from primary EY-audited data. IFRS 15/16 adjustments, revenue segmentation, margin trend analysis |
| Safaricom Power BI Dashboard | Power BI, DAX | 20 DAX measures, 5-page executive report, bookmark navigation across a decade of financial data |
| Olist SQL Analysis | PostgreSQL 17 | 100K+ e-commerce transactions. Cohort retention, logistics performance, seller and category segmentation |
| Olist Power BI Dashboard | Power BI, DAX | Live PostgreSQL 17 connection, revenue, customer behaviour, and logistics KPIs across 5 report pages |
| Superstore Sales Analysis | Excel | Power Query pipeline, PivotTable analysis, KPI dashboard, ranked business recommendations |
- BSc Economics — Kenyatta University (2026)
- Field data analyst — UNICEF Kenya and ILO project work
- Finance and operations — Flekc Freight and Logistics
- Revenue analysis — Truce Lounge
- Freelance web development and data analytics
- Life OS — Personal management app in React and Supabase (Goals, Finances, Habits, Spiritual, Fitness modules)
- Dira — AI-powered SME operations platform targeting African small businesses, NGOs, and county governments
- Deepening Python for data analysis and automation with n8n