13 days ago

AVP Acquisition Fraud Strategy and Model Monitoring

Synchrony

On Site
Full Time
$157,500
New York, NY
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Job Overview

Job TitleAVP Acquisition Fraud Strategy and Model Monitoring
Job TypeFull Time
Offered Salary$157,500
LocationNew York, NY
Map of New York, NY

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Job Description

Role Summary/Purpose

The AVP, Acquisition Fraud Strategy and Model Monitoring, is a multi-functional role within the credit fraud acquisitions strategy team. The primary responsibilities include overseeing the performance of fraud models and conducting in-depth data analytics to identify underlying model performance issues and developing action plans for deteriorating models. The role will work closely with the Acquisition Fraud Strategy Model Developers as well as the Credit Strategy Validation team to create remediation plans when models used in Credit strategies are not performing as expected. Additional responsibilities include supporting the evaluation of new fraud models, fraud and technology tools, coordinating model roll-outs with the strategy team, as well as developing enhanced ongoing monitoring reporting.  The AVP, Acquisition Fraud Strategy and Model Monitoring will report to the VP, Acquisition Fraud Strategy.

Essential Responsibilities

  • Conduct deep dives and root cause analysis on deteriorating models to identify underlying issues.
  • Develop tactical and strategic action plans to address model performance issues.
  • Author narratives for on-going model monitoring executive summaries explaining technical concepts in easily understood language.
  • Develop thorough and detailed documentation to support the strategy team’s model development process to ensure consistency, transparency, and alignment with organizational goals.
  • Develop enhanced reporting to support fraud model performance monitoring.
  • Work cross functionally with fraud strategy leads to support their analytics of fraud strategies and models.
  • Work closely with the implementation team to ensure that Acquisition Fraud Strategic goals are met and remove obstacles to meet those goals.
  • Perform model implementation validations and ensure strategies have the use of the best available tools and scores.
  • Support evaluating new fraud models and tools that can be leveraged in acquisitions, payments, and merchant underwriting.
  • Assist fraud strategy leads in the development of fraud strategies and analytics when time permits.
  • Partner with advanced modeling teams to drive targeting/treatment solutions that meet business objectives.
  • Collaborate with 2nd / 3rd line to ensure strong governance, safety & soundness of strategies. Fully support regulatory requests, internal reviews, audits and business continuity planning.
  • Partner with portfolio credit managers and client teams to launch new initiatives, communicate changes in a timely & effective manner, and ensure strategies are driving the desired P&L impacts.
  • Partner with compliance, legal, fair lending and audit as required.
  • Perform ad hoc analytics, validations, and remediations as required.
  • Perform other duties and/or special projects as assigned.

Qualifications/Requirements

  • Bachelor’s degree and 5+ years of experience building analytically derived strategies within Credit, Marketing, Risk or Collections in Financial services, or in lieu of a Bachelor's degree, 9+ years of experience building analytically derived strategies in Marketing, Risk or Collections in Financial services.
  • 3+ years of experience working with statistical tools such as SAS, Python, Tableau.
  • Expert level proficiency with Excel.
  • 3+ years of experience in retail, business, installment loans, or private label credit.
  • Excellent temperament and ability to work through uncertainty, collaborate respectfully across functions & teams, and find solutions to issues.
  • Ability and flexibility to travel for business as required.

Desired Characteristics

  • Experience operating at a strategic level as part of a cross-functional team.
  • Use of advanced technical & analytical competencies in driving effective strategic goals within a significant functional area.
  • Strong understanding of the consumer credit lending lifecycle and card programs.
  • Strong understanding of fraud models and their usage with fraud strategies.
  • Strong understanding of model evaluation metrics such as precision, recall, F1.
  • Familiarity with modeling approaches such as logistic regression and tree ensembles.
  • Understanding of the Lines of Defense (2nd Line Strategy Validation and 3rd Line Internal Audit).
  • Excellent oral and written communication skills with impact and influence.
  • Ability to multi-task and perform in a fast-paced environment.
  • Experience working alongside and in unison with off-shore teams.
  • Demonstrated ability to manage multiple projects, organize work flow and timelines.
  • Master’s Degree or MBA with advanced analytic focus, or equivalent advanced degree.

Key skills/competency

  • Fraud Strategy
  • Model Monitoring
  • Data Analytics
  • SAS
  • Python
  • Tableau
  • Excel
  • Credit Risk
  • Financial Services
  • Risk Management

Tags:

AVP Acquisition Fraud Strategy
Model Monitoring
Fraud Analytics
Credit Risk
SAS
Python
Tableau
Financial Services
Strategy Development
Data Analysis
Risk Management
Excel
Consumer Credit
Model Validation
Acquisitions

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How to Get Hired at Synchrony

  • Tailor your resume: Highlight experience with credit, fraud, and analytics. Use keywords from the job description like 'SAS', 'Python', and 'model monitoring'.
  • Showcase strategic thinking: Emphasize your ability to develop action plans and conduct root cause analysis for model performance issues.
  • Quantify achievements: Provide specific examples of how your analytical strategies improved P&L impacts or reduced fraud.
  • Demonstrate collaboration: Detail experiences working cross-functionally with strategy, validation, and implementation teams.
  • Prepare for technical and behavioral questions: Be ready to discuss your experience with statistical tools and how you handle uncertainty.

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