Data Scientist [Multiple Positions Available]

JPMorgan Chase & Co.•Tempe, AZ

1d•Onsite

About The Position

This role involves partnering with Product Groups and Lines of Business to assess business drivers and underlying data. The Data Scientist will collaborate with business owners to formulate quantifiable goals, advise on strategies and analysis to achieve business insight for decisioning and prioritization, and execute KPIs, trend analysis, and other analytical techniques to improve business performance. The position requires collaboration across functions and lines of business to drive analytics, derive insights, and socialize results. Responsibilities include importing, cleaning, transforming, and validating data from multiple sources, assessing customer interactions across various channels to understand customer journeys and friction points, and reviewing banker engagement data with customer data to formulate engagement and journey insights. The role will leverage analytical applications to describe, analyze, and interpret trends in complex datasets and prepare and deliver presentations summarizing insights to executives. Collaboration with data management, strategy, and other analytics teams is essential. Additionally, the role will leverage large language models (LLM) and generative AI technologies for information processing and insight extraction, and utilize statistical methods for sampling and cohort identification to ensure reliable data collection.

Requirements

Master's degree in Business Analytics, Business Administration, Finance, Statistics, Machine Learning, or related field of study plus 1 year of experience in the job offered or as Data Scientist, Quant Analytics, Deputy Manager, or related occupation.
Alternatively, a Bachelor's degree in Business Analytics, Business Administration, Finance, Statistics, Machine Learning, or related field of study plus 3 years of experience in the job offered or as Data Scientist, Quant Analytics, Deputy Manager, or related occupation.
Utilizing Business Intelligence tools such as SQL, Python, or Alteryx to explore data, analyze information and formulate into insights, and assess field performance related to client satisfaction and portfolio growth.
Utilizing at least one programming language to extract data, develop data sets and flows, and optimize queries to produce efficient scripts.
Defining business KPIs with project partners and establishing analytical test and measurement frameworks through Python or SQL tools.
Designing approaches and presenting analytical insights to analytic and non-analytic functions to showcase results that answer field related questions with a focus on banker production including client interaction and portfolio growth, and sales including financial services products assisting clients with financial services needs.
Working through the full analytics lifecycle from requirements to execution and delivering results that assist with understanding banker production as well as banker driven financial services product sales.
Managing projects by engaging with and updating project partners, ensuring alignment, incorporating feedback, and providing transparency throughout the project lifecycle, tracking projects efforts through Excel and PowerPoint, and providing regular project updates through email.
Utilizing Excel pivots, VLOOKUP, and aggregation formulas such as "sum" or "Count" to assist with insights and reports to be leveraged by stakeholders.
Utilizing PowerPoint add-ons for presentation templates, designs, and data visualizations and preparing materials for outside audiences.
Using Advanced Statistical methods and concepts, such as regression, predictive modeling, time series forecasting, or text mining, including developing datasets that can feed into packages, assessing which analytical concept to execute based on business requests, and testing and validating results.
Using Cloud and Big Data platforms such as Snowflake to access data and the available functionality and to complete tasks and projects by navigating datasets within a data ecosystem, creating temporary tables for processes, and pivoting results by utilizing the platform functionality.

Responsibilities

Partner with Product Groups and Lines of Business to assess business drivers and underlying data.
Collaborate with business owners to formulate quantifiable goals.
Advise on strategies and analysis to achieve business insight for decisioning and prioritization.
Execute KPIs, trend analysis, and analyses, including segmentations, optimizations and other techniques to improve business performance.
Collaborate across functions and lines of business to drive analytics.
Derive insights and socialization of results.
Import, clean, transform and validate data from multiple sources in preparation for analytics.
Assess customer interactions and events across a variety of channels (calls, branch, online, mobile) to understand customer journeys and friction points.
Review banker engagement data with customer data to help formulate engagement and journey insights.
Leverage a variety of analytical applications to describe, analyze, and interpret trends and patterns in complex data sets.
Prepare and deliver presentations summarizing sharp insights and conclusions to executives.
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 information, extracting valuable insights and trends to inform data-driven decision-making.
Utilize statistical methods to effectively sample and identify appropriate cohorts, ensuring representative and reliable data collection for comprehensive analysis.