Transaction Monitoring- Analytics
Role Overview
PwC is seeking skilled professionals to support its leading banking client on Transaction Monitoring engagements. The role requires strong analytical skills with AML domain knowledge. The candidate will work at the intersection of financial crime compliance, data science, and regulatory risk management.
Key Responsibilities
1. Transaction Monitoring & AML
- Perform validation of AML Transaction Monitoring scenarios (e.g., structuring, layering, mule activity, TBML, velocity, round-tripping).
- Analyze alert performance metrics (false positives, SAR conversion, hit rates).
- Support regulatory-aligned documentation and governance processes.
- Review STR/SAR data to assess detection effectiveness.
2. Data Analysis & Data Science
- Perform large-scale transactional data analysis to identify behavioral patterns and typologies.
- Conduct statistical testing, sensitivity analysis, and segmentation.
- Develop and test data-driven calibration strategies.
- Apply clustering, outlier detection, and behavioural modelling techniques where relevant.
- Create analytical dashboards and visualizations for stakeholder reporting.
3. ETL & Advanced Analytics
- Write complex SQL queries to extract, transform, and validate AML datasets.
- Perform data reconciliation between source systems and AML platforms.
- Develop reusable ETL logic to recreate transaction monitoring scenarios.
- Conduct data quality checks and resolve inconsistencies.
- Use Python (Pandas, NumPy, SciPy, Scikit-Learn, Statsmodels, etc.) for:
- Perform advanced data modelling and statistical analysis.
- Automate data pipelines and analytical workflows.
- Work with large datasets using scalable tools
Required Skills & Experience
- 3+ years of experience in AML Transaction Monitoring within banking or consulting.
- Strong understanding of AML typologies (structuring, layering, mule accounts, TBML, cross-border risks).
- Hands-on experience in SQL for complex data extraction and transformation.
- Strong Python programming skills for advanced data analysis and modelling.
- Experience working with large-scale transactional datasets.
- Strong problem-solving and analytical thinking.
- Ability to translate regulatory and typology requirements into data-driven solutions.
- Experience preparing client-ready documentation and presentations.
- Ability to work in cross-functional teams across risk, compliance, and technology.
Preferred (Good to Have)
- Experience with SAS AML / Actimize / other AML platforms.
- Experience in threshold calibration or model validation engagements.
- Exposure to regulatory reviews (AUSTRAC / APRA / RBI / global regulators).
- Experience with distributed data processing (PySpark, MLlib).
