
Manager - Transaction Monitoring Tuning & Optimization
- Bangalore, Karnataka
- Permanent
- Full-time
- In connection with the Global Financial Crimes program
- Ability to independently manage, organize, and prioritize multiple tasks, projects and responsibilities
- Develop mathematical or statistical theory/models to interpret customer KYC data and historical transaction data to group customers and non-customers into segments and clusters in order to monitor their activity in the correct TM thresholds.
- Create statistical representative samples for ATL/BTL testing using hypergeometric sampling techniques in order to validate that the transaction monitoring model is effective and functioning accordingly.
- Process large amount of data for statistical modeling and graphic analysis.
- Conduct data profiling to validate relevant data and data sets to be used for customer segmentation and tuning initiatives.
- Support in the creation of detail documentation which includes scenario logic, identified tunable and static parameters and minimum values for all parameters.
- Analyze data and sample to ensure accuracy of key data elements for alert generation
- Knowledge of mathematics particularly statistics.
- Ability to code using R or Python for customer segmentation and data analytics.
- Ability to solve problems through mathematical and deductive reasoning.
- Familiarity implementing, testing or evaluating performance of financial crime and compliance systems.
- Proven track record of strong quantitative testing and statistical analysis techniques as it pertains to BSA/AML models, including name similarity matching, classification accuracy testing, unsupervised/supervised machine learning, neural networks, fuzzy logic matching, decision trees, etc.
- Familiarity of current compliance rules and regulations of the FRB, SEC, OCC, FATF, FinCEN, OFAC, and familiarity with USA PATRIOT Act, BSA/AML and OFAC screening regulations.
- Prior experience designing compliance program tuning and configuration methodologies, including what-if detection scenario analytics, excess over threshold, and sampling above/below-the-line (ATL/BTL) testing.
- Working knowledge of one or more of the following programming platforms: SAS, Matlab, R, Python, SQL, VBA, etc.
- Familiarity with vendor models like Actimize SAM, SAS, SearchSpace, Mantas, OTUS, or SIRON.
- Bachelor's degree in statistics, mathematics, quantitative analysis, economics, computer science, data and technology Sciences or related fields is required. Advance degree a plus.
- 8-10 years experience in designing, analyzing, testing and/or validating BSA/AML models, and/or OFAC sanctions screening models.
The MUFG Group is committed to providing equal employment opportunities to all applicants and employees and does not discriminate on the basis of race, colour, national origin, physical appearance, religion, gender expression, gender identity, sex, age, ancestry, marital status, disability, medical condition, sexual orientation, genetic information, or any other protected status of an individual or that individual's associates or relatives, or any other classification protected by the applicable laws.