Quant Analytics Associate Senior

JPMorgan Chase JPMorgan Chase · Banking · Wilmington, DE +1 · Consumer & Community Banking

Quant Analytics Associate Senior role at JPMorgan Chase within the Consumer and Community Banking division, focusing on Collections and Recovery Operations. The role leverages data governance, predictive analytics, data science, and machine learning to understand and predict customer behavior, optimize performance, and manage operational expenses. Responsibilities include data programming, trend monitoring, applying AI technology for efficiency, and collaborating across functions to implement strategies and mitigate risks. Requires intermediate to advanced knowledge in statistics, predictive modeling, and machine learning, with proficiency in SQL, SAS, R, Python, and visualization tools.

What you'd actually do

  1. Demonstrate robust data programming and analytical skills to efficiently collect, organize, analyze, and disseminate significant amounts of information with a high degree of attention to detail and accuracy.
  2. Monitor internal and external trends (customer/industry) and understand business drivers, underlying data and core operational processes to support strategic direction with independent and thoughtful insights.
  3. Leverage innovation, AI technology and design thinking to continually improve operational efficiency and resilience.
  4. Address issues with forward-looking solutions and collaborate across functions (Ops, Risk, Finance, Legal, Compliance, and Technology) to support design, testing and implementation of strategies to optimize return on investment and mitigate risks, amidst continuous change in an agile and demanding work environment.
  5. Interpret and present data clearly using narratives, visualizations, and context to convey insights and drive action.

Skills

Required

  • statistics
  • finance
  • analytics
  • predictive modeling
  • machine learning techniques
  • SQL
  • SAS
  • R
  • Python
  • Alteryx
  • relational databases
  • Oracle
  • Teradata
  • visualization tools
  • Tableau
  • logical reasoning
  • data analysis

Nice to have

  • PhD degree in a quantitative field
  • applied risk and/or analytical experience in a financial services related industry
  • Applied Collections and Recovery knowledge/experience in Auto, Card, Retail and/or Business Banking product

What the JD emphasized

  • predictive modeling
  • machine learning techniques
  • applied analytical experience
  • complex and large data environments
  • AI technology

Other signals

  • leverages data governance, predictive analytics, strategy development, data science and machine learning disciplines
  • understand and predict customer and industry behavior
  • implement strategies through experimentation
  • leverage innovation, AI technology and design thinking