Sr. Analyst, Credit Model Development

Position Overview

This role will be responsible for providing analytical/quantitative input to develop, document, implement and monitor the build of complex consumer fraud risk models. This successful candidate will use their business analysis, process, and quantitative knowledge to ensure business intent is matched with modeling outcomes, and document development decisions under SR117 guidelines. In addition to responsibilities on individual modeling projects, this role will be expected to work on adhoc projects as needed. Communicating these to leadership is essential. This is a great opportunity for a modeler/statistician/data analyst/programmer with experience in consumer fraud analysis. We offer a dynamic, collaborative team environment with a strong credit risk management culture.

Key Responsibilities

• Serve as a key contributor and lead developer for various models (XGBoost, LightGBM, Logistic Regression, GLM)
• Work within SYF's cloud‐based data and modeling platforms and tools to develop and refine models and support fraud strategies
• Perform in-depth analysis on large data sets, and prepare analysis and reports to support discussions on key analytics and model risks
• Support development, documentation, implementation and monitoring of true-name fraud, synthetic risk, and merchant risk models using SAS/Python
• Work closely within the credit and risk organization to validate accuracy and performance of statistical models and to identify issues requiring further investigation
• Assist in development/understanding of vendor models to ensure accuracy and relevancy
• Provide independent research and analysis to support the conceptual soundness of key models
• Liaise with the Synchrony Financial business teams to uncover and highlight model risk associated with models
• Keep pace with the latest developments in academia, regulatory environment, risk technology, and financial services industries to embrace change and drive cross‐functional improvements
• Perform other duties and/or special projects as assigned

Required Qualifications

• Bachelor's Degree (Masters preferred) in Mathematics/Statistics, Operations Research, Economics, Finance or another quantitative discipline
• 2+ years of experience in Consumer Lending statistical modeling/risk analytics, preferably related to credit cards, identity fraud, and true name fraud
• 2+ years of coding experience with SAS, Python, R or an equivalent tool within the past 5 years
• Proficiency in writing SQL queries for data analysis, automation, and reporting purposes
• Minimum of 2 years of experience working with data processing and analysis tools/packages such as Hive, PySpark, Numpy, Pandas, dplyr, Sparklyr, SparkR, Tidyverse, or Lubridate
• Strong ability to manipulate, transform, and analyze large datasets efficiently
• Excellent written and oral communication, project management skills, with the ability to manage multiple assignments effectively
• Ability and flexibility to travel for business as required

Preferred Qualifications

• Experience utilizing modeling techniques that include XGBoost, LightGBM, Logistic Regression, regularization techniques, model evaluation, and model monitoring
• Working knowledge of big data tools such as Hadoop HIVE, PIG, or Apache Spark
• Exposure to Amazon SageMaker, Amazon Bedrock, Amazon Redshift, Python, SAS, and Unix commands
• Understanding and application of regulatory requirements for model development (e.g., SR 11-7/OCC 2011-12)
• Ability to work effectively in a matrix organization
• Understanding of macro-economic conditions and competitor trends

Benefits & Perks

• Salary: 85,000.00 - 140,000.00 USD Annual
• Compensation: Annual bonus based on individual and company performance
• Salaries are adjusted according to market in CA, NY Metro, and Seattle