ResumeProblem first thinking
I try to explain what the work is for before getting lost in the technical details.
Data, AI, and automation portfolio
I build useful data tools.
I am Owen Nda Diche. I work across data science, AI, analytics, automation, and practical web based tools. I like building things that make messy information easier to understand, test, and use.
About me
I care about work that is practical, readable, and useful.
My projects usually start with a real question: what is happening, what might happen next, what should be automated, or how can the answer be made easier for someone else to use? From there, I build the analysis, model, dashboard, database, or app that best fits the problem.
I am still growing, but I like learning by building. This site shows the range of what I can put together: machine learning models, AI assisted tools, SQL projects, forecasting, automation workflows, reports, and live Streamlit apps.
Applied AI and data
Classification, forecasting, NLP, recommendation systems, dashboards, and automation.
Build and share
I like turning ideas into something visible: a live app, a notebook, a repo, or a clear report.
Skills
The toolkit I keep building with.
I do not want to be boxed into one narrow lane. I am building range across data, AI, automation, analytics, and product style delivery.
AI and machine learning
Classification, regression, NLP, recommendation systems, anomaly detection, evaluation, and model interpretation.
Scikit learnNLPPyTorch
AI tools and automation
I can build small tools that automate planning, routing, project setup, screening, recommendations, and repeatable workflows.
CodexWorkflow LogicStreamlit
Data systems and analytics
SQL, data cleaning, metric design, warehouse style modelling, dashboards, and business analysis.
SQLPythonPower BI
Business insight
I turn raw datasets into clearer stories around churn, revenue, operations, demand, behaviour, and performance.
EDADashboardsReporting
Forecasting and risk
Time series forecasting, risk scoring, anomaly detection, fraud detection, maintenance risk, and operational monitoring.
ForecastingRisk ModelsAnomalies
Automation and delivery
Streamlit apps, reusable project scaffolds, workflow tools, reports, and clear GitHub documentation.
AppsGitHubDocumentation
Featured projects
A few projects that show how I think and build.
I picked these because they show different sides of my work: data systems, AI automation, and machine learning applied to real problems.
Explore the full project library
I have grouped the work by AI apps, automation, prediction, analytics, data systems, forecasting, and risk detection.
