Data Analyst · Data Scientist · Product Analytics
Data is everywhere. Actionable insights aren't. I use analytics, AI, and automation to help businesses cut through the noise, optimizing processes, predicting outcomes, and turning data into a competitive edge.
A little about me
Most companies have more data than they know what to do with. I help them figure out what matters, automate the boring parts, and make sure insights actually get used.
What I do
Tools change. The goal stays the same: make data understandable and useful.
Clean, explore, segment, and interrogate datasets to uncover patterns, trends, and opportunities.
Python · SQL · BigQuery · ExcelBuild interactive reporting experiences that make complex business questions easy to explore.
Power BI · Looker Studio . MatplotlibApply statistical and ML techniques and design cloud workflows for reliable, scalable data.
Airbyte · GCP · AWS · ETLSelected work
A collection of analysis, dashboards, machine-learning projects, and data pipelines.
An interactive advertising performance dashboard designed to evaluate campaign effectiveness and return on advertising investment. It provides insights into ad spend, ROAS, campaign types, impressions, and other campaign performance indicators.
A comprehensive Looker Studio dashboard designed to analyze and visualize sales performance across electronics product categories in real time. The dashboard tracks key metrics including sales volume ($99.30M), profit ($22.91M), cost ($76.38M), and order volume (5.1K units), with detailed breakdowns by product category, brand performance, and supervisor productivity analysis.
This Power BI dashboard provides an in-depth analysis of Africa's tech funding landscape from 2010 to 2023. It highlights key metrics, including $13.6B in total funding, $7.14B in latest sector funding, and the dominance of Life Sciences with $2.1B in recent investments. Explore sectoral trends, funding distribution, and insights into investor impact across the continent..
Average revenue, regional trends & 43% outperformance insight
1,107 units · $32.5K profit · State filtering
An interactive Power BI dashboard designed to monitor key indicators from the USAID Upliftment Program, providing insights into safe water access, food security, child immunization, and other program outcomes.
Operational reporting
This project automates the creation of personalized operational reports from structured performance data, then delivers those reports directly to stakeholders/Field workers through the channels they already use,eliminating manual reporting work and ensuring insights reach the right people faster. The system ingests raw records, aggregates metrics by individual and location, calculates key performance trends, and uses a large language model to transform structured data into clear, actionable narrative summaries. The final output is a polished PDF report delivered directly via API to the relevant stakeholders.
This project involved developing a credit scoring system for individuals lacking access to traditional banking, leveraging alternative data sources like mobile phone usage, utility payments, and community-based lending behavior. The model used Random Forest to predict creditworthiness, achieving an accuracy of 60%. The analysis highlighted the potential for financial inclusion for traditionally underserved populations.
An in-depth analysis of global illicit drug supply chains, focusing on opioids, amphetamines, and cocaine, with insights into youth usage trends, production hotspots, and socio-economic impacts.
An automated cloud data pipeline to extract, transform, and visualize semiconductor market data using AWS services and Power BI.
This Power BI dashboard involved analyzing sales, revenue, and units sold data for an electronics retail store across 4 countries, with a focus on uncovering trends and actionable insights to optimize operational efficiency and decision-making.
A comprehensive Power BI visualizing pending purchase orders (billing/receipt) to identify delays, vendor performance, and trends, enabling actionable insights for procurement efficiency
$3.06M total · $31K avg/month · England leads at $350K
$16.1M Sales · $12.4M Cost · $9.0M Profit · Web-inspired design
This project leverages data from the Internal Displacement Monitoring Centre (IDMC) to analyze global displacement trends caused by natural disasters from 2008 to 2023. Through interactive Power BI dashboards, it showcases key insights, including the displacement of 13 million people in 2023, flood-induced displacements averaging 127,000 per event, and significant regional disparities like Sudan's rate being three times the global average. The analysis aims to support climate justice initiatives and enhance understanding of the human impact of environmental crises.
This Power BI project focuses on analyzing fuel consumption trends within an automobile dataset. Leveraging interactive visualizations, the report explores key metrics such as MPG (Miles Per Gallon), horsepower, and fuel type distribution across various car models and manufacturers
Conducted an analysis of data science job listings from job baords to predict role categories and identify trends in the industry. This project aimed to assist hiring managers/stakeholders in efficiently categorizing job roles and understanding the key attributes associated with various positions
Performed an analysis of automobile fuel consumption and CO2 emissions to predict emission levels based on various factors. The project aimed to identify key contributors to fuel efficiency and environmental impact of CO2 emissions, aiding manufacturers and policymakers in making informed decisions.
Python data analysis of the impact of rainwater harvesting systems on crop yields and drought resilience in semi-arid farming regions. The analysis provides insights into effective water management strategies.
This project aims to classify customers of a telecommunications provider into four predefined service usage groups using demographic data. By predicting group membership with K-Nearest Neighbors (KNN), the company can tailor offers for individual prospective customers.
This Looker Studio dashboard involved analyzing sales, revenue, costs, and profitability data for a fast food chain across multiple locations, with a focus on uncovering trends and actionable insights to optimize operational efficiency and decision-making.
This project presents an in-depth financial analysis of PharmaCrest, using Python to predict revenue trends. The analysis includes key financial performance indicators, including revenue, cost of production, variance, budgeting, and forecasting. This exploratory data analysis (EDA) was enhanced using ARIMA and Random Forest models to predict future revenue trends based on historical data.
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