Quant Analytics [Multiple Positions Available]

JPMorgan Chase & Co.•Plano, TX

2h•Onsite

About The Position

This role involves leading and executing analytical projects from proposal to presentation, collaborating with business managers to develop information suites (dashboards, reports, deep-dives), and crafting narratives about the fintech industry for senior leadership. The position requires serving as a subject matter expert in transaction, product, and customer data, providing enhanced data assets and consultation to the Data and Analytics organization. Key responsibilities include partnering with product teams to leverage quantitative analytics for business insights and product strategy influence, identifying opportunities to use AI/ML for product enhancement and operational efficiency, and conducting market research on industry trends and the competitive landscape. The role also demands continuous mastery of analytical techniques like causal inference and modeling, and developing/implementing analytical best practices for collaboration.

Requirements

Master's degree in Business Analytics, Data Science, Data Analytics, Statistics, Economics, Finance, Mathematics, Operations Research or related field of study plus 3 years (36 months) of experience in the job offered or as Quant Analytics, Data Science, Online Assortment Analytics, or related occupation.
Alternatively, a Bachelor's degree in Business Analytics, Data Science, Data Analytics, Statistics, Economics, Finance, Mathematics, Operations Research or related field of study plus 5 years (60 months) of experience in the job offered or as Quant Analytics, Data Science, Online Assortment Analytics, or related occupation.
Three (3) years of experience writing SQL queries, performing data manipulation, data structuring, and query optimization within large enterprise databases in financial or other consumer-oriented businesses.
One (1) year of experience delivering strategic analysis to leadership.
One (1) year of experience translating complex technical findings into consumable storylines in a fast-paced, dynamic environment.
Any amount of experience manipulating and wrangling multiple complex data sets to perform exploratory data analysis, identifying product and market opportunities.
Any amount of experience developing and maintaining dynamic and interactive dashboards using Tableau, leveraging data visualization, ETL automation, and ODBC connectors.
Any amount of experience designing and developing interactive Excel and PPT reports with advanced functionalities such as vlookup, index match, data analysis add-ons, or pivots for stakeholders to self-service.
Any amount of experience running analyses on products and consumers to guide product decisions.
Any amount of experience conducting statistical analysis and generating insights to guide business decisions.

Responsibilities

Independently lead and execute analytical projects end-to-end, from project proposal to presenting results to Senior Leadership.
Collaborate with business managers from product teams to develop information suites including dashboards, reports, and deep-dives.
Craft compelling narratives highlighting the current landscape of the fintech industry for C-suites.
Serve as a subject matter expert in understanding transaction, product and customer data, providing enhanced data assets and consultation to the broader Data and Analytics organization.
Partner with product teams, leveraging quantitative analytics to generate actionable business insights and influence product strategies.
Identify opportunities to leverage AI/ML tools to enhance product value proposition for customers and drive operational efficiency.
Conduct market research to stay informed about industry trends, emerging technologies, and competitive landscape in the financial sector.
Continuously master a broad range of analytical techniques such as causal inference or modeling and understand how to best apply them in solving each business problem.
Develop and implement analytical best practices including effective documentation and code hygiene to promote effective collaboration across teams in Data and Analytics.