AI, statistics, and operational analytics in one practical toolkit.

Theodore combines programming, machine learning, public-sector statistics, credit risk, and operational analysis.

Technical expertise

Practical AI and analytics capability across research and operations.

Theodore's work sits at the point where modelling skill, domain fluency, and public service meet.

Programming and analytics

PythonRSQLPower BIExcelData preprocessing

Machine learning

Deep learningCNNsRNNsSensor fusionPredictive modelling

Domain knowledge

Credit riskPublic-sector statisticsSupply chain logisticsHealthcare analytics

Applied capability

Technical depth is strongest when it is connected to a real decision.

Theodore's expertise is deliberately practical: he can build models, but he also understands committee reports, survey fieldwork, credit-risk conversations, and the pressure to make data useful.

Model builder

Comfortable moving from exploratory analysis to predictive modelling, including credit-risk models, deep learning, and sensor-fusion experimentation.

Public-data translator

Experienced turning administrative data, survey results, and community evidence into reports that committees and budget teams can use.

Operational analyst

Uses dashboards, workflow analysis, and performance metrics to reduce delays, improve tracking, and make progress visible to decision makers.

Map

Understand the decision

Start with the people who will use the evidence, the operational pressure they face, and the decision that must improve.

Model

Build the analytical system

Choose the simplest reliable statistical or AI method, document the assumptions, and keep the model explainable enough for its context.

Move

Turn analysis into action

Package insights through reports, dashboards, field coordination, or committee briefings so the work changes what happens next.