Kerja Sepenuh Masa Data Analyst (Banking - up to $8K), Gaji tinggi SGD 6,000 di PERSOL SINGAPORE PTE. LTD. Central Region (Singapore) - Maukerja

Business Function

• Group Legal, Compliance & Secretariat protects the bank’s reputation, capital, and stakeholder trust.

• This hands-on analytics role evaluates watchlist screening and matching systems used for customer and payment screening, including sanctions and PEP screening.

• The role applies data analysis and backtesting to develop tuning and rule proposals, assess their effectiveness and risk implications, and support stakeholder approval.

Key Responsibilities

• 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.

Candidate Requirements

• Bachelor’s degree or equivalent experience in Computer Science, Statistics, Engineering, Data Science, or another quantitative or technical field.

• 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.
  

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