Quant Analytics [Multiple Positions Available]

JPMorganChase•Wilmington, NC

16h•Onsite

About The Position

The Quant Analytics role involves collaborating with stakeholders to drive analytics, formulate quantifiable business cases, and assess business drivers. The position requires monitoring KPIs, performing trend analysis, and utilizing various analytical techniques to enhance business performance. Responsibilities include importing, cleaning, and transforming data from multiple sources, analyzing customer interactions across channels to understand journeys and friction points, and leveraging analytical applications to interpret complex data sets. The role also entails preparing and delivering presentations of insights to senior leadership, partnering with data management and strategy teams, and utilizing large language models (LLM) and generative AI for survey response analysis. Additionally, the role involves using statistical methods for survey audience sampling, incorporating additional data sets through team partnerships, and mentoring team members and stakeholders on survey data and results. Managing the book of work with management calibration is also a key duty.

Requirements

Master's degree in Business Analytics, Statistics, Machine Learning, or related field of study plus 1 year of experience in the job offered or as Quant Analytics, Quantitative Analyst, or related occupation.
Alternatively, a Bachelor's degree in Business Analytics, Statistics, Machine Learning, or related field of study plus 3 years of experience in the job offered or as Quant Analytics, Quantitative Analyst, or related occupation.
Developing quantifiable business goals and applying statistical and analytical methods to derive actionable insights for decision-making and prioritization.
Monitoring key performance indicators (KPIs) and initiatives, trend analysis, and analyses, including segmentations, optimizations and other techniques to improve business performance.
Collaborating with cross-functional teams to drive analytics initiatives and disseminate insights.
Importing, cleaning, transforming, and validating data from diverse sources using ETL (Extract, Transform, Load) processes to prepare for analysis.
Leveraging tools for Database querying including at least one of the following: SQL, Alteryx, Python, or R.
Leveraging statistical analysis tools to analyze data sets including at least one of the following: SQL, Alteryx, Python, or R.
Leveraging tools for Data retrieval including at least one of the following: SQL, Alteryx, Python, R, Tableau, or Adobe Analytics.
Developing and delivering executive-level presentations summarizing data insights and conclusions.
Processing and analyzing survey responses, and extracting insights and trends for data-driven decision-making.
Identifying and selecting representative survey audiences for reliable data collection and comprehensive analysis using statistical sampling methods.
Interpreting data and addressing business challenges through data-driven solutions.

Responsibilities

Collaborate with stakeholders across functions and LOBs to drive analytics and formulate quantifiable business cases.
Partner with Product Groups and Lines of Business to assess business drivers and underlying data.
Monitor KPIs/initiatives, trend analysis, and analyses, including segmentations, optimizations and other techniques to improve business performance.
Import, clean, transform and validate data from multiple sources in preparation for analytics.
Analyze customer interactions and events across a variety of channels (calls, branch, online, mobile) to understand customer journeys and friction points.
Leverage a variety of analytical applications to describe, analyze, and interpret trends and patterns in complex data sets.
Prepare and deliver presentations summarizing insights and conclusions to socialize to stakeholders and Senior leadership.
Partner and collaborate closely with data management teams, strategy teams, and other analytics resources across multiple functional teams.
Leverage large language models (LLM) and generative AI technologies to efficiently process and analyze survey responses, extracting valuable insights and trends to inform data-driven decision-making.
Utilize statistical methods to effectively sample and identify appropriate survey audiences, ensuring representative and reliable data collection for comprehensive analysis.
Leverage Data and Analytic Team partnerships for incorporating additional data sets for optimizing business results.
Act as a mentor to Team members, stakeholders and fellow Data and Analytics partners in survey data and results.
Manage book of work with management calibration.