I turn messy, large-scale data into decisions people can trust.
I'm a Data Analyst at Deloitte, using SQL, Python and PySpark to reconcile and analyse financial data for global clients, and building dashboards that drive faster decisions. I lead and mentor a team of analysts and contractors, and I'm expanding further into cloud data engineering and AI automation.
My path into data started with a BSc in Statistics, where I first learned to think in distributions, models and evidence. Since then I've worked across three organisations — WayForward, Deloitte's Team Administration function, and now Deloitte's Data Analytics team — each one adding a different layer to how I work: technical depth, stakeholder communication, and an understanding of how data supports real business and audit decisions.
Today, as a Data Analyst on Deloitte's Audit service line, I reconcile and analyse financial datasets exceeding a million records using SQL and PySpark in Azure Databricks, build automated data transformation workflows in Azure Synapse, and maintain dashboards in Tableau, Power BI and CRM Analytics that teams rely on to make decisions faster. I also lead and mentor a team of analysts and contractors — resolving technical queries, developing training and onboarding materials for the wider team, and interviewing new joiners into the Data Analytics team.
Alongside that, I'm expanding further into AWS, Airflow, dbt and AI automation — deepening the engineering side of my practice as I move toward Data & AI consulting.
A progression from stakeholder-facing operations into hands-on, large-scale data analysis.
Dashboards and analysis built in Tableau, Power BI and Python. Click through to explore the live dashboards where available.
An interactive Tableau dashboard giving HR a quick overview of headcount, department distribution, compliance training status and vacation usage across the company, modelled across three related tables.
A Tableau dashboard analysing $159M+ in revenue across 42,600+ customers and 126,000+ orders — breaking performance down by age, gender, state and month to surface where revenue is coming from.
A Power BI report comparing paid and unpaid maternity/paternity leave policies across 1,600+ companies and 51 industries, highlighting which sectors lead on parental leave provision.
A Power BI report comparing price, ratings and specs across 208 laptops from 19 brands, including a price-vs-rating correlation to test whether higher price means a better-rated product.
import pandas as pd
import logging
logging.basicConfig(filename='rides_log', level=logging.INFO)
logging.info('Starting data cleaning process')
try:
rides = pd.read_csv('rides.csv')
logging.info("Dataset loaded successfully")
except Exception as e:
logging.info(f'Failed to load dataset: {e}')
raise
rides['Vehicle Type'] = rides['Vehicle Type'].str.lstrip()
rides['Vehicle Type'] = rides['Vehicle Type'].fillna('unknown')A Python/Pandas script that cleans a raw rides dataset — trimming whitespace, standardising inconsistent categories, flagging and handling missing values, and zeroing out cancelled bookings — with logging at every step for traceability.
2023 · View certificate
2023 · View certificate
2024 · View certificate
2023 · View certificate
2023 · View certificate
2020
Federal University of Agriculture, Abeokuta, Ogun, Nigeria
Before and alongside data analytics, I've done a good amount of Salesforce consulting and business analysis work — it's part of how I learned to map processes, gather requirements and translate business needs into technical solutions.
Oct – Nov 2023. Implemented a Knowledge Base and self-help/FAQ/chatbot options for customer support, integrated telephony with Salesforce, and rolled out a multi-channel support system — cutting customer inquiries by ~20%, service requests by ~15%, and case resolution time by ~25%.
Sep – Oct 2023, with Clicked. Conducted stakeholder interviews to elicit requirements, mapped the Dreamforce Digital Engagement Team's process end-to-end, and crafted user stories and project plans for Salesforce-driven solutions — presenting findings to peers and industry professionals.
Open to Senior Data Analyst and Data Engineering conversations. The fastest way to reach me is email or LinkedIn.