AM- Banking and Capital Mkt-BFS024185

You will be primarily working for the centralized advanced analytics team of a banking firm to help develop leading edge AML models for transaction monitoring, name matching, watch-list monitoring, customer risk scoring as well as providing input to the framework for model development. The role will require interacting with various business units including their risk, finance, controllership stakeholders etc. You will also be responsible for coordinating with auditors and model development teams to ensure the AML and Enterprise Modeling Governance standards are followed; Your activities will include, but will not be limited to the following:
• Provide analytical support for recommending actions to mitigate risk and use judgment-based decision-making regarding AML policies and procedures
• Accomplish the objectives of the Enterprises’ AML Program through effective oversight and support of critical AML applications
• Assess the quality of the data for model development as well as inputs to the model, providing recommendations to improve the data quality at the source
• Developing models, testing, reviewing and performing validation activities and prepare end to end model documentation
• Propose recommendations to improve monitoring systems and capabilities based on identified risk and control gaps

Minimum Qualifications

Qualifications we seek in you
• 3+ Years of Experience in BFS Risk analytics preferably in AML area
• Minimum of a Master of Science in Statistics/Economics/Finance or Bachelor’s in Engineering, Computer Sciences, Information Management
• Experience in developing, validating models and risk management of anti-money laundering related models
• Experience in supporting independent review (IR) and challenge of different aspects of model (conceptual soundness, model performance etc.) across different AML model to a high degree of depth, as required by and detailed in the Bank's policies and standards
• Good knowledge of data analysis / analytics / mining techniques
• Sound knowledge of banking operations
• Hands on expertise in SQL, ETL, SAS, Python, R working with large data sets
• Good scripting and automation experience using SAS/Python/R etc
• Hands-on Experience in Statistical and Machine Learning models
• Good client management and communication/presentation skills – written & verbal
• Self-driven, proactive, “can-do” attitude. Ability to work under ambiguity and with minimal supervision

Preferred Qualifications
• AML/fraud analysis knowledge would be preferred
• Prior model development experiences would be preferred

Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. For more information, visit www.genpact.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube.