You will be responsible for gathering and analyzing large sets of fraud, risk and compliance data to build predictive models that are deployed in the FCRM platform. Working in a team environment you will work on a variety of models to reduce fraud, improve false positives and fine tune AML and Compliance reviews to make banks more efficient and effective using analytic techniques such as logistic regression, scorecards and predictive modeling techniques such as Neural Networktechnology. After building a high performing model, you will work with the technical team to deploy the models in real-time using tools such as ADAPA and PMML.
For internal purposes only, the business title for this position is Market Research Analyst, Advisory.
Essential Job Responsibilities:
•Build analytic models using a variety of techniques such as logistic regression, risk scorecards and pattern recognition technologies.
•Assist in the creation of Fiserv Fraud Consortium by working with customers to identify data sources, fraud and risk tagging and then collecting the data in a highly useable format for modeling.
•Analyze and understand large amounts of historical fraud and risk data to determine suitability for use in models and then work with staff scientist to segment the data, create variables, build models and test those models.
•Work with technical and development teams to deploy models in a cloud based environment.
•Build Model Performance Reports and Modeling Technical Documentation to support each of the models for the product line.
•Assist in building and maintaining API documents for each fraud model and work with the technical and development teams to ensure that models are deployable in real-time.
•Support Sales of FCRM products by providing analytic expertise in presentations to clients as needed.
•Support Sales and upgrades of products by managing retrospective data studies to run clients data through Fiserv models.
•Provide implementation support regarding analytic models as needed.
•Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, Mathematics or Information Technology
Job Related Experience:
Job ID R-10085324