Data Analyst - AML (Bank|Up to $6.5k)

The Job - Parse, transform, and analyse structured and unstructured screening data, including customer, identity, watchlist, payment-message, and transaction-party data, as applicable. - Compare new and existing watchlist screening and matching systems using defined datasets, scenarios, and effectiveness metrics. - Analyse differences in match generation, detection coverage, false-positive rates, data handling, and processing performance, and identify their root causes. - Develop tuning strategies and propose screening rules, parameters, or configuration changes based on analytical evidence. - Backtest proposed changes using historical and edge-case data to assess detection effectiveness, false-positive rates, operational impact, and residual risk. - Prepare evidence-based proposals for stakeholder approval, documenting the methodology, assumptions, options, expected benefits, limitations, operational impact, residual risk, recommendation, and rationale. - Define analytical datasets, test scenarios, data quality controls, and acceptance measures for comparative assessment. - Maintain reproducible analyses and clear traceability from source data and methods through tests, results, proposals, and decisions. - Develop dashboards and reports covering match volumes, false-positive rates, detection coverage, and processing performance. - Ensure analyses and proposals meet internal standards and are suitable for Compliance and audit review. The Talent - More than five years' relevant experience, with strong financial crime prevention and data analytics expertise. - Proficiency in Python is mandatory. Experience with enterprise analytical platforms such as CML or CDSW, and with big data or data warehousing, is desirable. - Proven experience parsing, transforming, and analysing large-scale structured and unstructured datasets is mandatory. Candidates must be able to identify patterns, explain outcomes, and work efficiently at scale. - Experience in screening-system comparison, tuning, rule development, and backtesting is required, including assessment of detection effectiveness, operational impact, and residual risk. - Strong knowledge of AML/CFT, watchlist screening, and name-matching concepts, including sanctions and PEP screening. Experience in customer or payment screening, and familiarity with the relevant data and matching attributes, is desirable. - Strong analytical, problem-solving, critical-thinking, and data-visualisation skills, with attention to data quality and reproducibility. - Ability to develop, document, and present clear, evidence-based proposals that balance detection benefits against false-positive rates, operational impact, limitations, and residual risk for stakeholder approval. - Experience using Jira or similar tools to manage requirements, test cases, and defects is desirable. Next Steps - Drop your resume and contact us to follow-up, or send your resume to cecilia.sim@adecco.com - Email Topic: Apply Data Analyst - Only shortlisted candidates will be contacted Cecilia Sim Xin Yang EA License No: 91C2918 Personnel Registration Number: R22105099

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