10+ years in financial services technology, with at least 4 years in trade surveillance, communication surveillance, or regulatory compliance technology
Demonstrated understanding of ASIC INFO 283, EU MAR/MiFID II, FCA SM&CR, and APAC regulatory frameworks
Hands-on experience with at least one major surveillance platform: NICE Actimize SURVEIL-X, Behavox, Shield FC, or NASDAQ SMARTS
Strong understanding of eComms detection models: market abuse, information barriers, conduct risk, off-channel evasion, and trade-comms correlation
Experience in Agile/SAFe delivery environments as a Product Owner or Business Analyst in regulated financial services
Ability to translate complex regulatory requirements into clear, testable user stories
·Bachelor’s degree in Computer Science, Finance, Law, or related discipline
Experience with Australian regulatory environment (ASIC, AUSTRAC, APRA) and Tier-1 Australian bank operations
Familiarity with ML/NLP concepts in communication surveillance (transformer models, lexicon-based detection, false positive reduction)
Certified SAFe Product Owner/Product Manager (POPM) or equivalent Agile certification
Experience with multi-jurisdiction surveillance programs spanning APAC, EMEA, and Americas
Surveillance platforms: NICE Actimize SURVEIL-X, Behavox, Shield FC, Global Relay, Smarsh, Theta Lake
Own and maintain the product backlog, translating ASIC INFO 283 requirements, EU MAR obligations, and FCA SM&CR mandates into prioritised user stories with clear acceptance criteria
Define the product vision and roadmap across three workstreams: vendor platform configuration, bespoke case management build, and ML detection model pipeline
Collaborate with compliance, legal, and front-office stakeholders to capture surveillance requirements across 6 jurisdictions (AU, EU, UK, SG, HK, NZ)
Work with ML engineers to define detection model requirements, acceptable false positive/false negative thresholds, and model benchmarking criteria aligned with ASIC’s guidance on alert calibration
Partner with the architecture team to validate that the eComms data pipeline meets data quality standards for downstream ML models
Drive sprint planning, refinement, and review ceremonies; ensure delivery velocity aligns with regulatory milestones
Define and track KPIs: alert precision, recall, false positive rates, mean review time, and model drift metrics
Liaise with vendor account teams on product roadmap alignment, licensing, and feature requests
Ensure 72-hour trade reconstruction capability is maintained and examination-ready at all times
Present progress, risk assessments, and roadmap updates to senior compliance leadership and CIO office