Quant Analytics [multiple Positions Available]

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

Develop and evaluate data collection methods, conduct research for marketing strategies, and drive analytics to grow card acquisitions and customer engagement. Analyze large datasets to support business growth, provide customer segmentation, and innovate using data mining and machine learning techniques. Collaborate with development teams to automate data integration and perform reporting for digital campaigns.

What you'd actually do

  1. Devise and evaluate methods and procedures for collecting data.
  2. Conduct research and recommend marketing strategies in the digital space to the card business.
  3. Drive analytics effort to grow new card acquisitions and existing customer's engagement on key digital marketing channels.
  4. Interface with cross- functional strategy teams to setup digital KPI's and drive the tracking and reporting in those channels.
  5. Help develop strategic roadmaps to achieve KPI's and drive the tracking and reporting in those channels.

Skills

Required

  • Leading performance measurement and analytics for clients in the financial services industry
  • Designing and developing interactive analytical reports in Microsoft Excel and PowerPoint utilizing functionalities including VLOOKUP, INDEX MATCH, array formulas, pivot tables, data analysis add-ons, dynamic filters, and embedded objects to automate data analysis and presentation workflows
  • Creating executive-ready presentations in Microsoft PowerPoint by integrating dynamic data visualizations, scenario analysis outputs, and automated links to Excel data
  • Querying structured datasets using SQL techniques including window functions, CTEs, and stored procedures for complex data manipulation, transformation, and in-depth analysis
  • Developing data visualizations using Tableau or Power BI by implementing calculated fields, parameter controls, real-time data integration, and advanced data cleaning to monitor KPIs and visualize business trends
  • Using Python libraries including pandas, and NumPy for complex data manipulation, transformation, and in-depth analysis
  • Applying statistical techniques including hypothesis testing z-test, ANOVA, and correlation analysis to assess the statistical significance of A/B experiments and providing data-driven recommendations that support strategic decision-making
  • Automating recurring reporting processes and building end-to-end data workflows in Alteryx using data blending, transformation, and custom macros to enable scalable and repeatable insight generation
  • Translating complex data into actionable insights for both technical and business stakeholders
  • Applying machine learning techniques including regression analysis, classification algorithms, cohort analysis, associative rule mining, and scenario simulation to evaluate business performance, predict outcomes, and track behavioral trends over time

What the JD emphasized

  • Master's degree in Business Analytics, Statistics, Economics, or related field of study plus two (2) years of experience
  • Bachelor's degree in Business Analytics, Statistics, Economics, or related field of study plus four (4) years of experience
  • Leading performance measurement and analytics for clients in the financial services industry
  • Designing and developing interactive analytical reports in Microsoft Excel and PowerPoint utilizing functionalities including VLOOKUP, INDEX MATCH, array formulas, pivot tables, data analysis add-ons, dynamic filters, and embedded objects to automate data analysis and presentation workflows
  • Creating executive-ready presentations in Microsoft PowerPoint by integrating dynamic data visualizations, scenario analysis outputs, and automated links to Excel data
  • Querying structured datasets using SQL techniques including window functions, CTEs, and stored procedures for complex data manipulation, transformation, and in-depth analysis
  • Developing data visualizations using Tableau or Power BI by implementing calculated fields, parameter controls, real-time data integration, and advanced data cleaning to monitor KPIs and visualize business trends
  • Using Python libraries including pandas, and NumPy for complex data manipulation, transformation, and in-depth analysis
  • Applying statistical techniques including hypothesis testing z-test, ANOVA, and correlation analysis to assess the statistical significance of A/B experiments and providing data-driven recommendations that support strategic decision-making
  • Automating recurring reporting processes and building end-to-end data workflows in Alteryx using data blending, transformation, and custom macros to enable scalable and repeatable insight generation
  • Translating complex data into actionable insights for both technical and business stakeholders
  • Applying machine learning techniques including regression analysis, classification algorithms, cohort analysis, associative rule mining, and scenario simulation to evaluate business performance, predict outcomes, and track behavioral trends over time