Quant Analytics Associate Senior - Fraud Strategy

🏢 JP Morgan
📍 OH, United StatesFull-timeOn-site
📅 Posted: 1w ago🔄 Updated: 1w ago
CV%
✨ AI Summary
The Quantitative Analytics Associate Senior on the Point of Sale Fraud team will manage and develop fraud risk strategies to minimize fraud losses and protect customers. Responsibilities include interpreting complex data, formulating strategies, identifying key risk indicators, and collaborating with cross-functional partners. The role requires a Bachelor's degree in a quantitative discipline, 3+ years of experience in fraud/risk/payments, and advanced proficiency in Python, SAS, and SQL. A Master's degree and experience with Machine Learning/LLMs are preferred. This role does not offer visa sponsorship.
Required Skills
Information Technology
PythonSASSQLData Extraction
Soft Skills & Professional Competencies
Analytical SkillsProblem SolvingCommunication
Other
interpersonal skills
Nice to have:
Information Technology
Machine LearningLarge Language Models
🎁 Benefits & Perks
Comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching.
Requirements
Bachelor's degree in a quantitative discipline or equivalent experience, plus 3+ years in fraud/risk/payments. Advanced Python, SAS, and SQL skills are required. Must be able to query large datasets, transform data into actionable insights, and deliver recommendations to management. Strong analytical, problem-solving, communication, and interpersonal skills are essential.
Description

Drive impactful fraud prevention as a Quantitative Analytics Associate on our Point of Sale Fraud team where your advanced risk analyses and strategic insights help reduce fraud losses, protect customers, and influence key decisions across the organization. 

As a Quantitative Analytics Associate II in the Point of Sale Fraud team, you will manage fraud risk strategies in the Fraud Policy area and perform complex risk analyses with the objective of reducing fraud related losses while balancing customer impact. You will frequently interact and communicate with cross-functional partners and communicate and present presentations to managers and executives.

Job responsibilities

  • Interpret large amounts of complex data to formulate problem statement, concise conclusions regarding underlying risk dynamics, trends, and opportunities
  • Manage, develop, communicate, and implement optimal fraud strategies (including rules, cutoffs, policies, operational flows, etc.) to protect the bank from fraud related losses and improve customer experience at Point of Sale
  • Identify key risk indicators and metrics, develop key metrics, enhance reporting, and identify new areas of analytic focus to better capture fraud.
  • Provide subject matter expertise on strategy implementation/testing and initiatives related to the improvement of risk mitigation processes and infrastructure
  • Collaborate with cross-functional partners to understand and address key business challenges
  • Own fraud strategy initiatives end-to-end—define the problem, perform analysis, support implementation, and run pre/post-performance assessments.
  • Identify business opportunity by performing well thought analysis – Data mining, ensuring data integrity, synthesizing and communicating findings to senior management
  • Assist team efforts in the critical development of new fraud pattern or spending pattern detection tools while providing clear/concise oral and written communication across various functions and levels, inclusive of Operations, IT, and Risk Management

 

Required qualifications, capabilities, and skills

  • Bachelor's degree (or related work experience) in a quantitative discipline in a financial services organization, plus 3 or more years’ experience in fraud/risk/payments or related field.
  • Advanced understanding of Python, SAS, and SQL.
  • Ability to query large amounts of data and transform raw data into actionable management information.
  • Strong analytical and problem-solving abilities.
  • Experience delivering recommendations to management.
  • Self-starter with the ability to drive for resolution.
  • Strong communication and interpersonal skills with the ability to interact with individuals across departments/functions and with senior-level executives.

 

Preferred qualifications, capabilities, and skills

  • Master's degree (or related work experience) in a quantitative discipline, preferably in a financial services organization, plus 3 or more years’ experience in fraud/risk/payments or related field.
  • Experience with Machine Learning technologies and knowledge of LLMs.

 

This role is not eligible for visa sponsorship. Sponsorship includes, but is not limited to, support for I-983 training plans, F-1/OPT or CPT, H-1B, and any other employment authorization or immigration-related action requiring JPMorganChase sponsorship or intervention.

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🎯 Overalli74%
⚡ Skillsi85%
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Ontology Match: 85.0
Matched:✓ Requirements Matching✓ Ontology Skills Mapping
📜 Eligibilityi49%
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Local: 19600%
🏗️ Career Fiti91%
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Seniority: 91.0
📋 Requirementsi67%
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Domain: 67.0
🔥 Motivationi78%
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Title Fit: 78.00