Analyst-Risk Management

Team Overview:
The Financial Crime - Centre of Excellence team is responsible for the Enterprise-Wide AML transaction monitoring programs across all our products and services for US and International markets. The team develops, implements and monitors the automated transaction monitoring strategies/rules, reports, and other processes designed to identify activity potentially indicative of money laundering or other financial crime behavior that is important from Regulator Perspective.

How will you make an impact in this role
The successful candidate will be responsible for partnering with GFCC, FCSU, GRC Capabilities teams to design and implement automated transaction monitoring (TM) scenarios to support market compliance (LECO) stakeholders and align regarding the management of the company s compliance risk.

• Academic Background: Bachelor s degree or master s degree from a Tier -1 Institute
• Past Experience: Minimum of 1 year of relevant work experience
• Experience using Excel, SQL/HQL, and Statistical Programming (Python)
• Strong verbal and written communication skills, with the ability to translate between various technical and non-technical audiences
• Proactive and reactive thinking and good analytical skills
• Excellent critical thinking and attention to detail
• Excellent planning and organizations skills including ability to manage inter-dependencies and execute under stringent timelines
• Exceptional drive and commitment; ability to work and thrive in in fast changing, results driven environment; and proven ability in handling competing priorities
• Proactive learner with the ability to quickly learn new concepts and techniques with minimal supervision
• Knowledge of AML Investigations, and/or the payments industry is a plus. Working knowledge of Credit and Fraud Risk is extremely preferred
  

• Defining and documenting business requirements, in cohort with Stakeholders
• Providing conceptual support for the design of TM scenarios involving credit and charge cards
• Performing data analysis using Excel pivot tables, intermediate SQL queries, and/or statistical techniques (e.g. Exploratory Data Analysis using Python)
• Ensuring process and actions are logged and support regulatory reporting, documenting the analysis and the rule build in form of qualitative document for relevant stakeholders
• Analyze the effectiveness of the existing TM rules and propose optimization wherever required
  Reviewing output to ensure conformity and accuracy with their intended design