UA

About

Senior.
Specific.
Delivery-focused.

I am a Principal Data Scientist with deep experience in banking, fraud analytics, financial crime, and enterprise AI. My work spans the full delivery lifecycle — from problem framing with stakeholders to deploying production solutions and presenting outcomes to leadership.

What I do

I design and deliver network analytics frameworks for mule account and fraud network detection.

I build GenAI assistants for credit policy navigation, memo generation, and risk intelligence monitoring.

I develop fraud detection models across origination and behavioural domains, with governance and explainability built in.

I lead training programs that build lasting AI and data science capability inside banking teams.

How I work

Start with the decision
Every model and pipeline is anchored to a business decision. If the output doesn't change how someone acts, it has no value.
Governance from day one
In regulated environments, a model that cannot be explained is a liability. Explainability is designed in, not added afterwards.
Complexity hidden at the interface
Graph models, LLMs, and feature pipelines are powerful tools. The end user should see clarity, not machinery.
Training amplifies everything
Organisations that invest in building data literacy across teams outperform those that rely on a single analytics resource.

Focus Areas

Financial Crime AnalyticsFraud Detection & ScoringNetwork Link AnalysisGenAI AssistantsCredit Risk AutomationRisk IntelligenceData Science TrainingEnterprise AI AdoptionModel GovernanceGraph Analytics

Let's work on something important.

Open to senior data science, AI strategy, and risk intelligence opportunities.

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