Manager- Sanctions Screening & Optimization

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About the Role
Position Title: GFC Sanctions Screening Tuning Team - Manager
Corporate Title: AVP
Reporting to: VP – Global Financial Crimes Sanctions Design, Tuning and Optimization
Location: Bangalore
Job Profile
Purpose of Role
This new position has been created to establish GFCD's for the purpose of establishing GFCD Operations Intelligence & Analytics capabilities for BTMU. One of several key positions in the new Global Financial Crimes Division Operations function, this position will be responsible for (1) threshold tuning, (2) optimization of rules tuning and existing filter platform to improve effectiveness and efficiency, (3) create and execute test cases and scripts for testing of changes and releases (4) create tailor business rules to reduce hit rate, prepare tuning data, reviewing hit reduction strategies (5) identify and mitigate sanctions risks through periodic risk assessment on algorithms and rules. The incumbent is responsible for supporting leadership to ensure a globally consistent effort that enables continuing improvement to the sanctions screening capabilities and further mitigate potential financial crime.
Main Responsibilities
In connection with the Global Financial Crimes program –
Ability to independently manage, organize, and prioritize multiple tasks, projects and responsibilities
Create and execute test cases and scripts for testing of changes and releases
Create tailored business rules to reduce hit rates, prepare tuning data, reviewing hit reduction strategies
Plan, design, develop/implement code/configuration for Sanctions screening application;
Identify and mitigate sanctions risks through periodic risk assessment on algorithms and rules;
Perform data analysis to determine and verify business requirements/issues specification, flows and deliverables for projects.
Produce meaningful reports from output of Sanctions screening for reporting to senior management
Create statistical representative samples for ATL/BTL testing in order to validate that the sanctions screening model is effective and functioning accordingly.
Process large amounts of data for statistical modeling and graphic analysis.
Perform model validation, memorializing model selection rationales and defined assumptions.
Develop and test experimental designs, sampling techniques, and analytical methods in order to monitor new typologies and emerging risks.
Develop data mining methodologies, including logistic regression, random forest, xgboost and Bayesian networks
Help develop of models involving tuning, calibration, segmentation and optimization.
Support the development of policies and procedures for sanctions screening life cycle.
Coordinate with regional Intelligence & Analytics teams to implement the global model.
Work collaboratively across functional teams within GFCD to ensure effective and efficient operations with clearly defined roles and responsibilities.
Candidate Profile
Skills and knowledge
Knowledge of Sanction Screening Optimization and Tuning.
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 Hotscan, Actimize SAM/WLF, SearchSpace, RDC, Bridger Insight, ACE Pelican, TCH OFAC Screening (EPN), FICO Credit/Debit, Guardian Analytics, and ThreatMetrix.
Strong knowledge about model risk management and associated regulatory requirements
Bachelor's degree in statistics, mathematics, quantitative analysis, economics or related field is required. Advanced degree preferred.
Experience interacting with the Executive Committee Leadership, control function leadership, and compliance subject matter experts
Proven excellence in execution in complex and demanding situations
Collaborative with strong interpersonal communication skills
Systemic thinker across enterprise
Process oriented coupled with a strong ability to develop appropriate program enhancing strategies
Detail-oriented and organized execution
Executive level presentation skills
An Enterprise Risk Management perspective
Additional skills
Experience interfacing with banking regulators and enforcement staff
Thorough understanding of an effective financial crimes risk management framework
Demonstrated ability to manage multiple projects simultaneously
The ability to interact effectively at all levels of the organization, including Bank staff, management, directors and prudential regulators
Ability to work autonomously and initiate and prioritize own work
Ability to work with teams of project managers
Solid judgment, strong negotiating skills, and a practical approach to implementation – including knowledge of Bank systems
Ability to balance regulatory requirements with the best interests of the Bank and its customers
Ability to prepare analytical reports and visual representation of information.
Ability to apply mathematical principles or statistical approaches where needed to solve problems.
Education & professional qualifications
Bachelor’s Degree (B.A.) from a four-year college or university
Master’s or Doctoral degree in Statistics a plus.
Experience
8-10 years’ experience designing, analyzing, testing and/or validating BSA/AML models, and/or OFAC sanctions screening models.
Mitsubishi UFJ Financial Group (MUFG) is an equal opportunity employer. We view our employees as our key assets as they are fundamental to our long-term growth and success. MUFG is committed to hiring based on merit and organsational fit, regardless of race, religion or gender.