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Data Analyst with less than a year in SQL, Power BI, and Python.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Engineering graduate and Data Analyst with a background in industrial operations. Proficient in Microsoft Excel, SQL, Power BI, and Python, with a track record of analyzing large datasets to uncover patterns, generate actionable insights, and support data-driven decision-making. I Bring a rare combination of engineering domain knowledge and data analytics skills - able to understand both the technical environment and the numbers behind it.
University of Benin (UNIBEN)
Bachelor of Engineering · Engineering
August 1, 2017 – June 30, 2022
AgricTech Training Platform - Database Design
June 21, 2026 – Present
Designed a normalized 7-table relational database schema (Programs, Students, Trainers, Courses, Enrollments, Farm Projects, Resources) with foreign key constraints enforcing referential integrity throughout. Modelled a many-to-many relationship between Students and Courses via a junction table (Course_Enrollments). Enforced data quality at the schema level using ENUM constraints, UNIQUE email fields, AUTO_INCREMENT primary keys, and NOT NULL rules.
Pizza Sales Analysis
June 21, 2026 – Present
Built a MySQL database and wrote SQL queries to extract KPIs: total revenue ($817.86K), average order value ($38.31), total pizzas sold (49,574) across 21,350 total orders. Performed time-series analysis using DAYNAME() and MONTHNAME() to identify Friday as the peak sales day and January/March as peak months. Analysed revenue by pizza category and size, finding Classic (26.91%) and Large pizzas (45.89%) drove the most sales; identified top and bottom 5 pizzas by revenue, quantity, and orders. Designed a two-page interactive Power BI dashboard with slicers, KPI cards, bar charts, and donut charts for non-technical stakeholders.
FIFA Players Data Analysis
June 21, 2026 – Present
Cleaned and processed a FIFA dataset of over 18,000 player records and 77 variables, handling missing values, correcting data types, and standardizing inconsistent entries using power query. Performed exploratory data analysis (EDA) to identify trends in player ratings, wages, and positional strengths. Built interactive Power BI dashboards to visualize player performance and market value distribution.
Bank Customer Churn Analysis
June 21, 2026 – Present
Analysed a 10,000-customer dataset across 7 business questions, validating data integrity before identifying that German customers churned at nearly double the rate of French customers and the 46-60 age group had a 51.1% churn rate. Segmented churn by tenure, credit score, geography, and active membership using CASE statements. Quantified revenue risk. Delivered 5 key findings with actionable recommendations including a Germany-specific retention strategy and a shift from customer acquisition to retention.
Cultural Fit Analysis
The candidate's projects show a diverse application of data analysis skills across different domains (sales, finance, sports, education database design). Their involvement in student organizations and tech events indicates a proactive and collaborative attitude, which generally aligns well with a positive cultural fit. The focus on practical, project-based learning suggests a self-starter mentality.
Soft Skills & Operational Fit
The candidate demonstrates good communication through clear project descriptions. Their involvement in organizing tech events and leading student societies suggests leadership, teamwork, and organizational skills. The projects indicate a problem-solving mindset and an ability to deliver actionable insights, which are valuable for operational fit in a data-driven role.