Lead Data Scientist, Fraud & Financial Crime
Financial Services Institution
The Opportunity
A leading financial institution is seeking a Lead Data Scientist to act as senior technical authority for fraud and financial-crime data science. This is a lead individual-contributor and technical leadership role where you'll set the direction across a portfolio of detection, monitoring and investigation capabilities.
The portfolio spans transaction monitoring, suspicious matter investigations, scams, AML/CTF, entity resolution, typology and network analysis, anomaly detection, NLP, Generative AI, neural networks and GNNs.
What You'll Be Doing
- Define and maintain the domain data science roadmap, anticipating shifts in criminal behaviour, regulation, data and technology, and turning them into evidence-based priorities
- Establish reference approaches and common standards across rules, statistical detection, classical ML, graph analytics, GNNs, NLP and GenAI
- Resolve consequential choices on entity resolution, graph construction, temporal validation, thresholds and human decision rights; sponsor dynamic graphs, embeddings and hybrid rules-plus-ML systems
- Set direction for GenAI and agentic applications
- Review high-risk models, graphs, prompts and decision policies before material release; set enterprise standards for leakage prevention, calibration and rare-event metrics
- Lead Responsible AI, Model Risk, AML/CTF and audit assurance as senior technical counterpart to legal, compliance and second-line partners
- Partner with financial-crime leadership and senior stakeholders on portfolio-level investment options, explaining uncertainty and trade-offs at the roadmap level
Lead Data Scientist , Fraud & Financial Crime
Financial Services Institution
The Opportunity
A leading financial institution is seeking a Lead Data Scientist to act as senior technical authority for fraud and financial-crime data science. This is a lead individual-contributor and technical leadership role where you'll set the direction across a portfolio of detection, monitoring and investigation capabilities.
The portfolio spans transaction monitoring, suspicious matter investigations, scams, AML/CTF, entity resolution, typology and network analysis, anomaly detection, NLP, Generative AI, neural networks and GNNs.
What You'll Be Doing
- Define and maintain the domain data science roadmap, anticipating shifts in criminal behaviour, regulation, data and technology, and turning them into evidence-based priorities
- Establish reference approaches and common standards across rules, statistical detection, classical ML, graph analytics, GNNs, NLP and GenAI
- Resolve consequential choices on entity resolution, graph construction, temporal validation, thresholds and human decision rights; sponsor dynamic graphs, embeddings and hybrid rules-plus-ML systems
- Set direction for GenAI and agentic applications
- Review high-risk models, graphs, prompts and decision policies before material release; set enterprise standards for leakage prevention, calibration and rare-event metrics
- Lead Responsible AI, Model Risk, AML/CTF and audit assurance as senior technical counterpart to legal, compliance and second-line partners
- Partner with financial-crime leadership and senior stakeholders on portfolio-level investment options, explaining uncertainty and trade-offs at the roadmap level
What You'll Bring
- Deep, sustained expertise in advanced analytics, statistics and ML, with a track record of technical leadership across multiple production use cases
- Advanced depth in at least one fraud/financial-crime specialism, with advanced breadth across several others (anomaly detection, graph/GNNs, entity resolution, NLP/GenAI, or human-in-the-loop decision design)
- Expert command of rare-event evaluation, temporal validation, calibration and champion-challenger testing,
- Extensive experience leading fraud/financial-crime solutions or portfolios in a large, complex, regulated organisation at a scale
- Advanced understanding of Responsible AI, Model Risk, AML/CTF and AUSTRAC expectations, with demonstrated capability representing the organisation to external regulators
- A record of influencing senior business, technology and risk stakeholders on material portfolio decisions , defining roadmaps and prioritising competing investments against measurable outcomes
Why Apply
This is a rare opportunity to shape enterprise-wide direction for fraud and financial-crime data science, owning analytical strategy and model assurance across a major regulated portfolio, while building lasting technical capability.
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