Job Description:

　　As a Quantitative Finance Analyst on the Enterprise Risk Analytics team, your main responsibilities will involve:

　　Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirementsMaintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risksUnderstanding and executing activities that form the end-to-end model development and use life cycleClearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology

　　Position Overview

　　Responsible for independently conducting quantitative analytics and modeling projects.Responsible for developing new models, analytic processes or systems approaches.Creates documentation for all activities and works with Technology staff in design of any system to run models developed.Incumbents possess excellent quantitative/analytic skills and a broad knowledge of financial markets and products.This role will support the AML Event Processor and respective team. The Event Processor is a consolidation engine that aggregates events from all detection channels and calculates aggregated risk scores for event groups based on individual risk factor scores.

　　Required Skills:

　　Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)2+ years of experience in model development, statistical work, data analytics or quantitative research or PhDStrong Programming skills e.g. R, Python, SAS, SQL or other languagesStrong analytical and problem-solving skills

　　Desired Skills:

　　Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniquesStrong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiencesExperience with large data setsEffective at prioritization/time and project managementBroad understanding of financial products

　　Shift:

　　1st shift (United States of America)

　　Hours Per Week:

　　40