BI Analyst — Oil & Gas & Operations

Peter
OgobaBusiness Intelligence

I am a Chemical Engineer and BI Analyst. My engineering background and field experience help me understand the real operations behind the data. From HSE incident costs to contract cash flow, ecommerce revenue patterns, and MTN telecom analysis, I enjoy turning raw data into simple, useful insights that support better decisions. After graduating from FUPRE with the Shell SPDC Merit Scholarship, I worked in O&G operations with Mansfield Energy Nigeria. That experience drives how I approach analytics — building dashboards that reflect real operational decisions, not just numbers on a screen.

5
Projects Built
4
Tools Mastered
B.Eng
Chemical Engineering
HSE
Certified Levels 1–3
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The analyst who knows the field.

I graduated with a degree in Chemical Engineering from FUPRE and received the Shell SPDC Merit Scholarship. I then spent a year working in O&G operations with Mansfield Energy Nigeria, supporting HSE compliance, equipment inspection, and safety reporting.

Working in that environment showed me how critical it is for data to reach decision-makers clearly and fast. I developed skills in Power BI, SQL, Python, and Excel — building projects across telecom operations, HSE analytics, ecommerce performance, and contractor finance. I focus on dashboards that reflect the actual work behind the numbers and give decision-makers clarity when it matters.

Education
B.Eng. Chemical Engineering — FUPRE, 2023
CGPA 4.35 / 5.00 — Second Class Upper
Scholarship
Shell SPDC JV Merit Scholarship — Full 5-year award on academic excellence
Certifications
HSE Levels 1, 2 & 3 — IAMPS
T-BOSIET — Offshore Safety
Data Analytics: Python & SQL
Field Experience
Technical Graduate Engineer — Mansfield Energy Nigeria Ltd, Rivers State (NYSC 2024–2025)
Availability
Open to freelance projects, consulting engagements & full-time roles — open to relocation
Stack

Tools & Technologies

Power Query
Data Modelling
KPI Design
Pandas
NumPy
ETL
HSE Analytics
Financial Analysis
Supply Chain BI
Storytelling

Selected Work

// Each project tells a story. Hover to explore.

Techbuild Dashboard
Contracts & Finance
01
Power BI DAX Financial Analytics

Techbuild Contractors Analysis

"Good contracts. Bad collections. The business is financing its own clients."

Techbuild holds ₦416.5M in contract value — yet actual profit sits at a negative ₦100.3M. This two-page Power BI analysis exposes exactly why: a 56.06% collection rate, ₦183M in outstanding receivables, and 25% of clients who have made zero payments to date.

What it enables

Management can immediately identify which clients pose zero-payment risk (Oilserve, Osubi Airport Authority, Local Energy Co-op), which contracts carry government dependency risk, and exactly which actions would recover ₦183M in cash flow. The insights page helps turn the data into a board-level decision document.

Power BI DAX Excel
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Safety Dashboard
HSE & Operations
02
Power BI HSE Analytics Oil & Gas

Safety Analytics Dashboard

"$24M in incident costs — but 79% of it was preventable."

Across 1,200 incidents and two years of data, this dashboard answers the question every HSE director needs to answer: where exactly is the money going, and why does it keep happening? The analysis covers incident costs by type and activity, root cause frequency, and corrective action compliance — all filterable by facility, department, shift, and risk category.

What it enables

Safety managers can see in one view that Poor Housekeeping is the leading root cause — not equipment failure, not fatigue — and redirect training budget, inspection time, and corrective action effort accordingly. Lost Time Injuries in Routine Operations represent the single largest cost category at $11.8M, giving operations directors a clear priority for intervention.

Power BI DAX HSE Data Cost Analysis
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Ecommerce Sales Dashboard
Ecommerce & Retail
03
Power BI Sales Analytics Multi-page Report

Ecommerce Sales Performance

"$5.5M in revenue — but which region, product, and channel is actually driving it?"

A 1-page Power BI report analysing ecommerce revenue performance across 2019–2021. With 20,000 orders, a $281 average order value, and four global regions.

What it enables

North America drives 52% of revenue but represents a concentration risk — over-reliance on a single region. The direct channel generates 15.7K orders versus Social Media's 0.3K, meaning the acquisition strategy is almost entirely organic, with significant untapped growth potential in other marketing channels. Revenue peaks every Q4 without exception, enabling confident seasonal planning. The 27-inch 4K gaming monitor alone generates $1.77M — nearly 32% of total revenue from a single product.

Power BI DAX Sales Analysis 1-Page Report
View Full Dashboard
MTN Executive Summary Dashboard
Telecom Operations
04
Power BI Python PostgreSQL Operational Intelligence

MTN Nigeria Telecom Operations Intelligence Dashboard

How can telecom leadership identify network performance issues, revenue collection risks, and customer experience challenges across Nigerian states?

Built a 5-page Power BI operational intelligence dashboard on a 10,000-customer telecom dataset using PostgreSQL, Python, and Power BI. The solution monitored revenue, collections risk, network quality, customer satisfaction, support demand, and payment behaviour across Nigeria.

Key Insights & Impact

• Identified states with below-average network quality and elevated call-drop rates.
• Quantified revenue exposure associated with overdue and unpaid customer segments.
• Highlighted regions combining poor customer experience and weak network performance.
• Developed a prioritisation framework for infrastructure improvement and customer retention initiatives.

Power BI DAX Python PostgreSQL 5-Page Dashboard
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ShopEase Ecommerce Profitability Analysis
Retail & Profitability
05
Excel Pivot Tables Profitability Analysis

ShopEase Ecommerce Profitability Analysis

"$300,900 in revenue and a healthy-looking 24.6% margin — but discounting past 20% is quietly cutting that margin in half."

An Excel pivot-table analysis of 1,000 ecommerce orders, breaking down $300,900 in revenue and $74,072 in profit across region, product category, customer segment, and discount level to find exactly where margin was being lost.

What it enables

Finance can see that discounting above 20% drops margin from roughly 41% to about 22%, giving a clear threshold for pricing policy. Electronics drives the largest profit in dollar terms but carries the lowest margin of any category, while the South region's shipping cost runs at 5.3% of revenue versus 2.9–3.6% elsewhere — an isolated, fixable cost leak. The Consumer segment generates the most revenue and profit but the lowest margin (29.2% vs. 36.9% for Corporate), flagging a margin risk as that segment continues to grow.

Excel Pivot Tables Profitability Analysis
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Contact

Let's work together.

Open to freelance projects, consulting work & full-time roles

peterogoba@gmail.com

Based in Warri, Nigeria — Open to relocation & remote

View Resume