Quant Analytics Associate

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

This role leverages data governance, predictive analytics, data science, and machine learning to support strategic initiatives in Collections and Recovery Operations within a financial services division. The associate will analyze data, monitor trends, and implement strategies to enhance performance and manage expenses, utilizing programming languages 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
  • Oracle
  • Teradata
  • Tableau
  • logical reasoning
  • data analysis
  • communication

Nice to have

  • Master's degree in relevant field
  • applied risk experience
  • analytical experience in a financial services related industry
  • Collections and Recovery knowledge/experience in Auto, Card, Retail and/or Business Banking product

What the JD emphasized

  • Beginner knowledge in statistics, finance, analytics, predictive modeling and machine learning techniques
  • 1+ years of applied analytical experience in complex and large data environments
  • Proven experience with programming languages (SQL, SAS, R, Python, Alteryx), relational databases (Oracle/Teradata), and visualization tools (Tableau)

Other signals

  • leverages data governance, predictive analytics, data science and machine learning disciplines
  • leverage innovation, AI technology and design thinking to continually improve operational efficiency
  • Beginner knowledge in statistics, finance, analytics, predictive modeling and machine learning techniques