- Data Analyst
- Internal Tools Builder
- Automation Engineer
I build systems that help operations scale.
I started in analytics and kept wanting to build what happens after the insight. At Afriex, a cross-border payments platform, that became Retool apps, AI workflows and lifecycle pipelines for Support, Treasury, Compliance and Operations.
Results at Afriex
The platform: 600,000+ active users, 50+ countries, $600M+ in annual payment volume.
- $5M+in transaction volume recovered within 4 months by a customer win-back I led the analytics for.
- 81,000+QA records captured in the first year of the Support app I built. The old spreadsheet held about 40,000 in three years.
- 3+ hourssaved every day for the Treasury team by an AI system that finds the best FX rates and flags arbitrage.
Selected work
Every project says where it ran and what data it used, so you know what you're looking at.
- Independent buildRead the case study
Account statement generator
Support teams ask for customer account statements all day, and the workflow behind them failed in silence. I rebuilt it as one tested engine with three ways in: plain-English Slack requests, a web tool and an API. Each returns a branded PDF and CSV.
About 5 seconds from request to PDF and CSV, with 109 tests passing.
TypeScriptNext.jsVercel
Trigger.devPostgreSQL - Production at AfriexRead the case study
Customer Support QA app
Customer Support tracked agent QA reviews in a spreadsheet that was slow, messy and sometimes crashed, so people avoided it. I rebuilt the workflow as a Retool app on Postgres, migrated the history, and built coaching analytics into it.
81,000+ QA records in the first year, against about 40,000 across the previous three.
RetoolPostgreSQLSQL - Production at AfriexRead the case study
Treasury FX intelligence
FX rates arrived in dozens of WhatsApp and Telegram groups, so Treasury had no single view of who was offering what. I built an AI system that turns those messages into structured data, finds the best rates and flags arbitrage.
Saves Treasury 3+ hours a day, and runs autonomously after testing against real trades.
AI extractionGoogle SheetsSlack - Production at AfriexRead the case study
Win-back and lifecycle
I led the analytics that found churned, high-value customers worth winning back. The business acted on it and recovered $5M+ in transaction volume within four months. Alongside it, I built the Snowflake to Customer.io pipeline behind lifecycle campaigns.
$5M+ in transaction volume recovered within 4 months.
SnowflakeCustomer.ioSQL - Fictional company, synthetic dataRead the case study
SendFast analytics case study
A leadership analysis of one quarter of transfers and signups for SendFast, a fictional Canada and Nigeria remittance company. SQL and Python show a loyal customer base, shrinking transfer values, and a signup funnel that leaks at KYC.
Five findings and three recommendations, delivered as a 12-slide leadership deck.
PythonpandasSQLiteJupytermatplotlib
Experience
One company, three years, and a title that kept catching up with the work.
Data Analyst, Automation & Internal Tools
Oct 2023 to present
Afriex, remote
Afriex is a B2C and B2B cross-border payments platform: fast, low-cost international transfers, virtual cards and multi-currency accounts for individuals, merchants and businesses.
- Led the analytics behind a high-value customer win-back that helped recover $5M+ in transaction volume within 4 months, then turned the approach into a repeatable retention workflow.
- Rebuilt a slow, chaotic Customer Support QA process as a Retool app with coaching analytics: 81,000+ records in year one and 5+ hours saved a week.
- Deployed a production AI system for FX intelligence that saves Treasury 3+ hours a day, and ran it autonomously after testing against real trading outcomes.
- Built lifecycle workflows on a Snowflake to Customer.io reverse ETL pipeline, powering feature-adoption campaigns and weekly activity summaries for B2B customers.
Data Analyst Intern
Apr 2023 to Oct 2023
Afriex, remote
Same company, first year. Started in SQL and grew into building.
- Built an AML monitoring automation for Compliance: SQL and Postgres rules flag accounts over risk thresholds, surfaced in Retool with Slack alerts, replacing manual reviews.
- Used SQL and Python to investigate production logs, audit payment flows and reconcile Stripe records.
- Co-owned automation and tooling work across Operations, Compliance, Product, Engineering, Finance and Growth.
Braze Customer Engagement Certification
B.Sc. Business Management, University of Uyo, Nigeria (2023)
Tools I work in
Chosen per problem. SQL and Python for the analysis, Retool and n8n when a team needs a tool fast, TypeScript when it needs to be built properly.
Data and code
Automation and internal tools
Trigger.devZapierClaude CodeNext.jsVercelSupabaseBI and CRM
Also used: Slack, Power BI, Customer.io, Braze, Attio, Loxo, Clay, Instantly, HeyReach, Prospeo.
Also built
- Sample data
Google Ads performance report
An interactive Looker Studio dashboard on sample Google Ads data (Mar 2023): cost against budget, clicks, impressions, conversions, cost per conversion, period-on-period change, and an ad-level drill-down.
Open the live report
- In progress
Google Play lead engine
Turns the Google Play Store into a structured B2B lead source. Filter apps by category, install velocity, ratings or SDK signals, resolve listings to parent companies and decision-makers, then enrich them for outbound. TypeScript npm package and CLI. Built, with a public demo still to come.
- Independent build
Self-hosted Trigger.dev and Supabase
My own automation infrastructure, secured with HTTP Basic Auth and GitHub OAuth, with scheduled weekly cron tasks that keep the databases active.