PMO / Data & Research Analyst — NHIA, Abuja

I reconcile the claim against the record, until the numbers agree.

I'm a data analyst working inside Nigeria's National Health Insurance Authority, where I turn claims backlogs, HMO submissions and enrolment data into dashboards and reports a steering committee can act on. Before NHIA, I reconciled payment records at Jumia, built BI dashboards remotely for a UK data team, and ran analytics for logistics and procurement teams in the oil & gas sector.

VERIFIED 6 PROJECTS · 2025
195facilities onboarded onto the CEmONC programme
₦287.7M+in claims cost reconciled across two TPAs
3,053enrollees tracked in one state programme audit
444facility records tested for statistical significance
40%gain in project visibility from an NHIA-wide tracker I built

Case files

01 — 06
FILE NO. CEMOC–TPA/2025

Claims dashboard & reconciliation, Leadway & United Health TPAs

VERIFIED

Built the live monitoring dashboard for NHIA's CEmONC maternal health programme, consolidating claims submitted by two Third-Party Administrators across 53 reporting facilities. The dashboard tracks approvals, rejections and pending items in near real time for the programme's steering committee.

53facilities reporting
1,414total beneficiaries
1,354claims verified
₦287.7Mapproved cost of services
Excel / Power Query Dashboard design Claims reconciliation TPA reporting
Dashboard for Leadway and United Health TPAs 2025, showing facility, beneficiary and claims totals
FILE NO. AXA–MANSARD/2025

AXA Mansard claims audit — summary vs. detailed report disparity

FLAGGED

Cross-checked AXA Mansard's summary claims report against its detailed submission and found the two didn't agree: the summary listed claims for 37 facilities while the detailed report covered only 22, leaving 15 facilities' claims unaccounted for. Logged every discrepancy by facility and issued a formal data request back to the HMO.

37 → 22facilities: summary vs. detailed
15facilities missing from detail
2,181claims re-verified in comparison
117claims rejected on review
Data auditing Error logging Facility-level QA
FILE NO. RIV-ENROL/2025

Rivers State enrolment & revenue report, NHIA

VERIFIED

Built the annual enrolment analysis for NHIA Rivers State, segmenting Gifship (group, individual, family) and Mop-Up registrations by month, and tying enrolment volume to revenue across four income streams.

3,053total enrollees for the year
1,990Gifship enrollees
1,063Mop-Up enrollees
₦63.46Mtotal programme revenue
Pivot modelling Excel Revenue analysis
FILE NO. NFFP-CLAIMS/2025

Fistula Free Programme (NFFP) consolidated claims reporting

VERIFIED

Consolidated patient-level surgical claims from six VVF (fistula) treatment centres into a single reporting sheet, then compared each facility's previous and most recent submissions month by month to catch late or missing claims before they reached the programme total.

6treatment centres consolidated
1,054patient admissions reconciled
10 mo.of submissions compared
Data consolidation Patient-level QA Excel
FILE NO. STAT-CASE/2024

Immunisation & delivery statistics — hypothesis testing case study

ANALYSIS

Independent case study on Nigerian facility-level immunisation and delivery data. Tested whether Penta3 vaccine coverage differs between facilities with high vs. low skilled-birth-attendance (SBA) rates, then modelled the relationship between SBA and Penta3 coverage with correlation and regression, choosing non-parametric tests where normality assumptions failed.

n = 444valid facility records
p = 0.0012Mann-Whitney U, coverage gap
ρ = 0.265Spearman correlation, SBA × Penta3
R² = 0.029variance explained by regression
Hypothesis testing Mann-Whitney U Spearman correlation Regression
FILE NO. SIDE-PROJECT/BI

Chelsea FC all-time performance dashboard

VERIFIED

A personal Power BI project outside of work: an interactive, filterable dashboard covering every historical Chelsea FC result by opposition, letting you slice results-to-date against any of 24 opponents and see the win/draw/loss split update live.

54games played vs. Man City (sample view)
50%win rate
24filterable opponents
Power BI DAX Interactive filtering
Chelsea FC all-time dashboard in Power BI, showing games played, won, drawn and lost against a selected opposition

Experience

2019 — PRESENT
Jan 2025 — Present

PMO Analyst (Data & Research Analyst)

National Health Insurance Authority (NHIA), Abuja

Built the centralised project tracker for NHIA's active health insurance initiatives, lifting cross-team visibility by 40%, and ship weekly executive dashboards that cut leadership response time by 25%.

2024 — 2025

Data Analyst

High Impact Careers, UK (Remote)

Deployed automated Power BI dashboards that cut manual reporting time by 40%, and used SQL to query, clean and migrate data across systems.

2023 — 2024

Admin & Operations Executive (Data-Driven Role)

Quest Oil Group, Lagos

Analysed sales and supply trends behind a 200% revenue increase from data-backed vendor selection, and ran procurement analytics on contract terms.

2021

Junior Data Analyst & Reconciliation Officer

Jumia Nigeria, Lagos

Reconciled rider payment records, catching discrepancies that improved payment processing time by 20%, and shipped the weekly/monthly ops reports used for forecasting.

Approach & toolkit

01

Reconcile before you report

Every dashboard starts by cross-checking submissions against each other — summary vs. detail, previous vs. recent — before a single number gets published.

02

Log the disagreement

Discrepancies get a formal error log with a colour-coded reference key, so the source of a data problem is traceable, not just flagged.

03

Test, don't assume

Where a claim about the data matters, it gets a proper hypothesis test and the correct one for the data's shape — not a default t-test.

04

Build for the reader

Dashboards are built for the person in the steering committee meeting, not the analyst — one screen, the numbers that matter, nothing to dig through.

Power BI SQL (MySQL / PostgreSQL) Excel — Advanced Functions, PivotTables Google Sheets Looker Studio Python (Beginner) Tableau (Introductory) Data Wrangling & Cleaning

Have a dataset that needs to add up?

Open to data analyst roles and short-term reporting or dashboard projects in health, insurance and programme monitoring.