I spent the first half of my career being confused about why dashboards kept lying. Then I realised the dashboard was never the problem. It was always the pipeline upstream.
Fixing that has kept me busy ever since.
How I got here.
I started early-career at Guaranty Trust Bank in Edo, Nigeria, on the customer-facing side, in a Customer Information Services role. Most of the day was front-line work: account enquiries, transaction disputes, helping customers onto self-service channels, logging complaints. What stayed with me wasn't the work itself but a pattern I kept noticing. People would walk in upset about an app that, technically, was fine. The transactions were going through. The product was working. But the dashboard the complaints team was reading told a different story, and that story was the one shaping decisions. That was the first time I saw clearly that most business problems sitting on someone's desk are data problems wearing a costume.
A few years later I joined the Federal Mortgage Bank of Nigeria in Abuja, Nigeria, as a Strategic Data Insights Analyst in the Asset Creation Unit of the Loan Administration group. The work was on the data side of mortgage origination at federal scale: dashboards, account reconciliations, portfolio reports, the queries and analyses that turned loan-book data into something senior leadership could act on. The output was real, the supervision was close, and the scale was bigger than anything I had worked with before. By the time I left I had seen the same pipeline-versus-dashboard pattern I had noticed at GTBank confirmed at federal scale, and I knew the work I wanted to do for the rest of my career was on the data side.
In 2020 I moved to Istanbul, Türkiye, to read for my MSc in Big Data Analytics and Management at Bahcesehir University. Three years of distributed systems, cloud, market analytics, and a thesis I genuinely loved: a recommender for football scouting across five European leagues. Football has always been a thinking habit for me, so building the technical version of that instinct felt natural. Alongside the MSc, I joined Microsoft's Learn Student Ambassador programme for nearly three years, ran Azure workshops, organised a hackathon, and grew the chapter on campus.
After the Bahcesehir MSc I took 17 months to widen the stack. Google Cloud, IBM, LinkedIn Learning. Statistics, R, BigQuery, Tableau, design thinking. I open-sourced a recommender system and a SQL Server schema during that window. The certifications matter less than the habit it built: if a tool is the right tool for the job, I will learn it on weekends rather than make excuses.
In mid-2024 I joined Natural Clinic in Istanbul, Türkiye, as their CRM Data Specialist. This was my first proper end-to-end ownership role. The CRM had grown organically over the years, and the marketing and sales teams were ready for a more reliable foundation underneath it. I rebuilt it from the ground up: cleaned the records, wired the marketing stack into a coherent flow, and put live dashboards in front of teams that had previously been working from static, manually refreshed reports. The work taught me that data quality is mostly a trust problem, and trust gets built one reliable report at a time.
Most recently I worked as an Analytics Engineer at Force24, a marketing automation SaaS in Leeds, UK. I built the data layer for their account intelligence platform from scratch and contributed across the rest of the stack into a live production environment. The lead feature I designed is built on a conviction I keep coming back to: dashboards should drive action, not just display data.
Alongside Force24, I wrapped my MSc dissertation at the University of Salford in Manchester. A research project I scoped, owned, and built end-to-end: an agentic ELT platform for customer intelligence in a live B2B SaaS environment under NDA. It is the work I would point to first when someone asks about my data science range, and it is where I planted a flag on a question I care about: how analytics should drive action, not just describe what happened.
What I'm doing now.
The Force24 contract and the Salford dissertation both wrapped in April. Since then I've been building independent industry projects, taking the patterns I tested in the dissertation and the Force24 work and turning them into enterprise-grade solutions in the agentic and analytics space. Practical, production-shaped, the kind of work I want to keep doing.
Alongside that, I'm moving deeper into AI engineering. Working through certifications in the space, sharpening the parts of the stack where agentic systems actually meet real data infrastructure. Six months from now I want to be the person on a team who can speak both languages fluently.
Open to conversations with teams building in that direction.
What I'm looking for.
An Analytics Engineer or Data Scientist seat on a team that takes data quality seriously, ships to production, and wants to do more than rebuild last quarter's dashboard. I care about clean modelling, opinionated tooling, machine learning systems that explain themselves, and making the analysts and product teams downstream of me faster. I am happy on the messy plumbing nobody else wants to touch, because that is usually where the value is.
Open to roles in Germany, the wider EMEA region, the UK, and remote across EU and UK time zones.
Education
- University of Salford · Manchester, UK · MSc Data Science · January 2025 to May 2026
- Bahcesehir University · Istanbul, Türkiye · MSc Big Data Analytics and Management · 2020 to 2023 · GPA 3.67 / 4.00
- University of Benin · Edo, Nigeria · BEng Computer Engineering · 2011 to 2017
Certifications
| Engineer Data for Predictive Modeling with BigQuery ML | Google Cloud |
| Python for Data Science and AI | IBM / Coursera |
| Generative AI for Business Leaders | Coursera |
| Tableau for Data Scientists | LinkedIn Learning |
| R for Data Science: Analysis and Visualization | LinkedIn Learning |
| Statistics Foundations 1 to 4 | LinkedIn Learning |
| Enterprise Design Thinking Practitioner | IBM |
| Enterprise Design Thinking Team Essentials for AI | IBM |
| Enterprise Design Thinking Co-Creator | IBM |
Off the clock.
A handful of things that aren't on a CV but are still part of how I think.
Bayern Munich, lifelong. Started watching in the Oliver Kahn era and never looked back. Tried to model my own game on Philipp Lahm: quiet, positionally relentless, never the loudest voice on the pitch but always the one holding the shape. Always had time for Ballack's number 13 too. I follow Bundesliga closely but watch across leagues, and I keep an eye on Nigeria and Germany at the international level. The football brain runs deep enough that the Bahcesehir thesis came directly from it: I have always had a knack for spotting talent before it reaches the first team, and the thesis was the technical version of that instinct. Don't be surprised to hear me talking up a prodigy who hasn't debuted yet.
Modern philosophy and unfiltered cultural commentary. Mark Manson is a regular, Everything Is Fucked in particular. I read across that whole territory: the writers who refuse to varnish how the world actually works, from Scott Galloway's takes on business and culture to memoirs like Jordan Belfort's. Whatever the mood asks for, really. I'm a podcast person too: Steven Bartlett's Diary of a CEO, Afropolitan, a rotating set of others.
Istanbul, then Manchester. Five years in Türkiye left a mark. I miss the chaos, the chai, the food, and the everyday sense that anyone you meet might be from somewhere you'd never guess; the melting pot ran at a different intensity there. Manchester is the chill counterweight. The large Nigerian community here makes it feel like home, and Britain and Nigeria share enough Commonwealth-era wiring that the cultural edges line up in ways I find genuinely interesting.
Music as a working tool. Afrobeats, rap, R&B, reggae, dancehall, pop: the rotation depends entirely on the mood. Tems and Wizkid for laid-back work. Sean Paul when the energy needs to come up. Jahmiel when I want something with a bit of weight to it. I genuinely think the right music makes me faster.
Connector by default. I'm usually the common link in a group, the one introducing people who turn out to be exactly what each other needed. I love being well-rounded enough to surprise people with what I know about, and I love learning from people who know more than I do about the things I haven't gotten to yet. I'll drop a proverb mid-conversation like I lived with my ancestors. Currently want to learn chess properly, and I owe my old football boots a return.
One small opinion. Sushi is overrated. I've tried, repeatedly. I don't get it.