AML Watchlist Analytics Specialist

PERSOL SINGAPORE PTE. LTD.; Singapore; Vor Ort; SGD 90.000 - 150.000; Vollzeit

Zusammenfassung

PERSOL Singapore Pte Ltd is seeking a hands-on analytics professional to evaluate watchlist screening and matching systems for customer and payment screening. The role applies data analysis and backtesting to tune rules and assess risk, with stakeholder alignment across Compliance.

You will develop datasets, perform backtests, and create dashboards showing detection coverage, false positives, and processing performance. Strong Python and AML knowledge required.

Qualifikationen

• Bachelor’s degree or equivalent in a quantitative field.
• 5+ years in financial crime analytics and data science.
• Proficiency in Python mandatory; experience with big data platforms desirable.
• Experience in screening systems, tuning, and backtesting.
• Strong knowledge of AML/CFT and sanctions/PEP screening.

Aufgaben

• Parse, transform, and analyse screening data, including customer and transaction data.
• Compare watchlist systems using defined datasets, scenarios, and metrics.
• Analyse differences in match generation, coverage, false positives, and performance.
• Develop tuning strategies and propose screening rules based on evidence.
• Backtest changes to assess detection, FP rate, and residual risk.
• Prepare evidence-based proposals for stakeholder approval with rationale.
• Define datasets, test scenarios, data quality controls, and acceptance measures.
• Maintain reproducible analyses with traceability from data to decisions.
• Develop dashboards and reports on match volumes, FP rates, and performance.
• Ensure analyses meet internal standards for Compliance and audit review.

Kenntnisse

Python

Data analytics

AML/CFT concepts

Large-scale data analysis

Problem solving

Ausbildung

Bachelor’s degree in CS/Statistics/Engineering/Data Science

Tools

Jira

Jobbeschreibung

PERSOL Singapore Pte Ltd is seeking a hands-on analytics professional to evaluate watchlist screening and matching systems for customer and payment screening. The role applies data analysis and backtesting to tune rules and assess risk, with stakeholder alignment across Compliance.

You will develop datasets, perform backtests, and create dashboards showing detection coverage, false positives, and processing performance. Strong Python and AML knowledge required.