Strategic Analytics - Associate

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Consumer & Community Banking

This role focuses on developing and implementing data-driven strategies and machine learning models to prevent digital fraud in financial services. The associate will analyze large datasets, design business rules, monitor trends, and collaborate with technical teams to build fraud-fighting products, ultimately protecting customers and reducing losses.

What you'd actually do

  1. Analyze large and complex datasets to uncover trends and behaviors in digital fraud activity.
  2. Develop and implement creative, data-driven strategies and business rules to reduce fraud losses.
  3. Monitor fraud trends and proactively identify emerging risks and vulnerabilities.
  4. Design and automate processes to improve the efficiency and effectiveness of fraud alert systems.
  5. Collaborate with technical and business partners to develop and implement new fraud-fighting products using agile methodologies.

Skills

Required

  • Python
  • SAS
  • R
  • SQL
  • Excel
  • PowerPoint
  • analytical programming
  • data analysis
  • experiment design
  • presentation skills
  • critical thinking
  • team collaboration
  • adaptability

Nice to have

  • digital payments
  • fraud prevention
  • financial services
  • machine learning models
  • agile project management
  • P&L management
  • product development
  • data integration
  • customer experience improvement

What the JD emphasized

  • Minimum 2 years of professional experience in analytics, risk management, or data science.
  • Proven ability to analyze and interpret large datasets and translate findings into actionable business strategies.
  • Familiarity with machine learning models and their application in fraud detection.

Other signals

  • Develop and implement creative, data-driven strategies and business rules to reduce fraud losses.
  • Collaborate with technical and business partners to develop and implement new fraud-fighting products using agile methodologies.
  • Familiarity with machine learning models and their application in fraud detection.