Sr. Analyst, Credit Model Development jobs in United States
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Synchrony · 3 hours ago

Sr. Analyst, Credit Model Development

Synchrony is a company that focuses on credit risk management and analytics. They are seeking a Senior Analyst to provide analytical input for developing and monitoring consumer fraud risk models while collaborating with various teams to ensure model accuracy and performance.

Consumer LendingFinanceFinancial ServicesInsuranceVenture Capital
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Growth Opportunities
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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 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 (vendor and in-house) and financial services industries to embrace change and drive improvements cross-functionally
Perform other duties and/or special projects as assigned

Qualification

Consumer Lending modelingSASPythonSQLData analysis toolsXGBoostLightGBMLogistic RegressionBig data toolsProject managementCommunication skillsTeam collaboration

Required

Bachelor's Degree (Masters preferred) in Mathematics/Statistics, Operations Research, Economics, Finance or other 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 in coding with SAS, Python, R or other equivalent tool within the recent 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 and packages such as Hive, PySpark, Numpy Pandas, dplyr, Sparklyr, SparkR, Tidyverse, Lubridate or equivalent libraries
Strong ability to manipulate, transform, and analyze large datasets efficiently
Strong written/oral, project management skills, communication skills with the ability to manage multiple assignments effectively
Ability and flexibility to travel for business as required
You must be 18 years or older
You must have a high school diploma or equivalent
You must be willing to take a drug test, submit to a background investigation and submit fingerprints as part of the onboarding process
You must be able to satisfy the requirements of Section 19 of the Federal Deposit Insurance Act
Legal authorization to work in the U.S. is required

Preferred

Utilizing modeling techniques supporting one (or more) of the following: XGBoost, LightGBM, and Logistic Regression, Regularization techniques, Model Evaluation and Model Monitoring
Working knowledge in big data tools such as Hadoop HIVE, PIG or Apache Spark as plus
Exposure to Amazon SageMaker, Amazon Bedrock, Amazon Redshift, Python, SAS, Unix commands
The application of regulatory requirements for Model Development (e.g. SR 11-7/OCC 2011-12)
Ability to work in a matrix organization
Understanding of macro-economic conditions & competitor's trends

Company

Synchrony

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Synchrony is a consumer financial services company.

Funding

Current Stage
Public Company
Total Funding
$500M
2024-02-15Post Ipo Equity· $500M
2014-08-01IPO

Leadership Team

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Brian Doubles
President & CEO
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Raj Deol
SVP, Sam’s Club Marketing Leader
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Company data provided by crunchbase