Hello, I'm Prince
I’m Prince, a London-based data scientist specialising in machine learning and AI engineering. I help businesses turn complex data into clear decisions, anticipate outcomes and build AI tools that make everyday work easier. With a foundation in Statistics, I take work from defining the problem and preparing the data through to testing and deploying a usable solution.
Evaluated RAG · Cloud-deployed ML · Published research
BSc Statistics · MSc Data Science, York St John University
Open to work · Available now for a 9–12-month placement
Numbers are part of my story.
People give them a purpose.
My journey has taken me from studying Statistics at the University of Ibadan to studying Data Science at York St John University in London. Along the way, I've worked with agricultural data, taught mathematics and helped take financial literacy into communities.
University of Ibadan · 2019–2024
York St John University · London
Explore the problem, the build, the decisions and the evidence behind each project. Read the case studies here, try a demo, or inspect the code.
I removed a reranker after benchmarking showed added latency without better answer-quality scores on my evaluation set. The deployed assistant combines hybrid retrieval, citations and explicit refusals.
I separated the interface from inference, logged predictions in BigQuery and automated deployment. The result is an explainable risk service, not just a notebook.
When Serverless blocked Spark MLlib, I kept distributed preparation in Spark and modelled the aggregated data in scikit-learn.
Read the full case studyFrom analysis and model evaluation to APIs, cloud deployment and monitoring.
Python
R
SQL
Pandas
NumPy
Power BI
Matplotlib
scikit-learn
TensorFlow
XGBoost
RAG
LLM evaluation
Docker
FastAPI
Git
GitHub Actions
Google Cloud
Azure ML
BigQueryCleaned, validated and analysed agricultural field-trial data from 8+ experimental locations, preparing more than 15,000 observations in R for crop-yield and biometrics analysis.
Ran exploratory analysis and fitted linear and logistic regression models as part of statistical modelling training.
Data quality · R · Statistical modellingSupported 20+ further-education students with GCSE maths, problem-solving and exam preparation.
Teaching strengthened how I explain difficult ideas and adapt to different levels of understanding.
GCSE mathematics · Communication · EducationLed financial literacy outreach across more than 10 schools, markets and communities, helping bring practical financial education to wider audiences.
Coordinated people and outreach activities around a shared public-service goal.
Leadership · Financial literacy · Community outreachResearch rooted in my undergraduate work, using Bayesian survival analysis to study recovery and death outcomes in Nigerian COVID-19 data.
I love sport, from following the competition to exploring its uncertainty through my World Cup forecasting project. Hospitality work has also taken me into London's stadiums and event venues.
I contribute behind the scenes in church media and have volunteered as a mental health ambassador with the Asido Campus Network. Teaching, community work and team settings have all shaped how I listen and explain.
I’m open to work in data science, machine learning and AI engineering. I’m available now for a 9–12-month industry placement as part of my MSc at York St John University, with the start date and duration agreed with the employer and university. I’m also interested in job opportunities and collaborations.
princeokunade1@gmail.com