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Analytics Engineer with 3+ years in data product development, ETL, and ML.
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Business-facing Analytics Engineer who builds end-to-end data products — from ETL pipelines and SQL data models to ML prediction APIs and Power BI dashboards — and translates them into decisions that move business metrics. 3+ years of hands-on experience across healthcare, e-commerce, HR, and fintech data. Proficient in Python, SQL, Power BI, and FastAPI. Comfortable owning the full stack: ingest, clean, model, predict, visualise, and deploy.
Prince Audu Abubakar University
B.Sc. (Honours) · Geology
October 1, 2021 – October 1, 2021
Startup — MVP Stage
Data & Analytics Engineer
November 1, 2025 – Present
India
RespecTECH
Data Analyst
July 1, 2024 – November 1, 2025
Nigeria
Goldman Sachs (Forage)
Virtual Intern — Controllers Division
May 1, 2024 – May 1, 2024
India
National Centre for Remote Sensing (NYSC)
GIS Analyst
February 1, 2023 – December 1, 2023
Nigeria
Airbnb Market Intelligence & Price Prediction Platform
June 1, 2026 – Present
Built a full end-to-end analytics product: ETL pipeline ingesting raw Airbnb listing data into PostgreSQL, 15+ SQL analytics queries, XGBoost price prediction model, FastAPI /predict endpoint, 6-page Power BI dashboard, and 5-page Streamlit frontend — all Dockerised. Model predicts optimal listing price against neighbourhood benchmarks, enabling hosts to make data-driven pricing decisions. Designed a star schema with fact and dimension tables supporting both OLAP-style queries and ML feature engineering from the same data layer.
View ProjectNetflix Content & E-Commerce EDA — AnalystLab Africa Internship
June 1, 2026 – Present
Conducted structured exploratory data analysis on the Netflix titles dataset, profiling content distribution, genre trends, release patterns, and country-level production insights to surface business-relevant findings. Combined Netflix EDA with a parallel e-commerce dataset analysis, applying data cleaning, null-value handling, and univariate/bivariate analysis techniques across both domains. Delivered findings as a structured analytical report mapping data patterns to actionable content and business strategy recommendations.
Sales Pipeline Prediction API
June 1, 2026 – Present
Built a production ML API predicting sales deal outcomes (WON/LOST) with 72.8% accuracy and high ROC-AUC, deployed via FastAPI + Docker with single and batch prediction endpoints. Created an accompanying Power BI dashboard visualising pipeline health, win-rate by segment, and deal-stage conversion for the sales leadership team.
Customer Churn Prediction Model
June 1, 2026 – Present
Trained a logistic regression churn classifier achieving 85.8% AUC on a 10K+ customer dataset; migrated from Flask to FastAPI and deployed on Render. Feature importance analysis surfaced contract type and tenure as top churn drivers, enabling targeted retention intervention recommendations.
Inventory Reporting & Stock Analysis
June 1, 2026 – Present
Cleaned and transformed raw inventory and supplier data using CTEs and window functions; built an interactive Power BI dashboard tracking stockouts, stock levels, and inventory adjustments across product lines.
GlowMart Nigeria FMCG Analysis — SkillAhead Data Analytics Challenge 2026
January 1, 2026 – January 1, 2026
Analysed a fictional Nigerian FMCG brand dataset under competition conditions, identifying that the core business risk was flat revenue growth — not the widely assumed supply/sales conflict — and framed it as the winning counter-narrative. Used SQL for aggregation and trend analysis and Excel for visualisation; structured the presentation to lead with the business problem rather than the data, a deliberate storytelling decision that distinguished the submission.
AnalystLab Africa Internship Program — Batch B
AnalystLab Africa
June 1, 2026 – Present
Data Analytics Essentials
Cisco Networking Academy
June 1, 2026 – Present
SkillAhead Data Analytics Challenge 2026
SkillAhead
January 1, 2026 – Present
Goldman Sachs Controllers Job Simulation
Forage
January 1, 2024 – Present
Cultural Fit Analysis
The candidate demonstrates a strong drive for continuous learning and skill development through various certifications, internships, and personal projects. Their experience across different industries (healthcare, e-commerce, HR, fintech) and project types (personal, academic, internship) indicates adaptability and a broad interest in applying data solutions. The focus on delivering business value and making data-driven decisions aligns well with a results-oriented culture. The independent nature of many projects also suggests self-motivation and initiative.
Soft Skills & Operational Fit
The candidate's project descriptions and work experience highlight strong problem-solving skills, particularly in identifying core business risks and framing data-driven counter-narratives. Their ability to own the full data stack from ingestion to deployment, and to communicate findings to non-technical stakeholders, suggests good operational fit and business acumen. The emphasis on reducing manual reporting and automating processes indicates a proactive and efficiency-oriented mindset.