Quant Analytics, Senior Associate - Home Lending

JPMorgan Chase & Co.; Jacksonville (FL); On-site; USD 90,000 - 120,000; Full time

Job summary

JPMorgan Chase & Co. in the United States seeks a Quant Analytics, Senior Associate - Home Lending to translate data into actionable decisions that impact customers and the firm. You will source, integrate, and analyze data to uncover value and support growth across the home lending business.

You will build dashboards and collaborate across teams to deliver analytics solutions for complex challenges. Advanced SQL and Python are essential, with experience in KPI tracking and stakeholder-focused

Qualifications

• Bachelor’s degree and 4+ years in analytics role.
• Advanced SQL across multiple sources.
• Strong Python to automate workflows and reporting.
• Experience defining, tracking, and evaluating KPIs; strong storytelling with data.

Responsibilities

• Partner with Sales, Marketing, Product, Finance, and Data & Analytics to align on priorities and deliver data-driven solutions.
• Source and integrate data from multiple platforms for reliable performance measurement.
• Perform descriptive, diagnostic, and predictive analyses to identify trends and actionable insights.
• Develop narratives that explain what happened, why, and what actions to take next.
• Quantify drivers of performance and recommend KPI improvements.
• Build analytical frameworks to support strategic initiatives.
• Design, automate, and maintain interactive dashboards for KPI tracking.
• Identify opportunities to enhance BI tooling and self-service reporting.
• Translate analyses into actionable recommendations for senior stakeholders.
• Collaborate on AI/ML solutions to automate processes and develop new capabilities.

Skills

Advanced SQL

Python

Data visualization

KPI tracking

Stakeholder communication

Cloud platforms

Generative AI prompting

Data integration

Education

Bachelor’s degree in a related field

Master’s degree in a related field

Tools

Snowflake

AWS

BI tools

Job description

Help shape the future of our home lending business by turning data into decisions that create better outcomes for customers and the firm. You’ll take on high-impact, strategic questions, work side-by-side with cross-functional partners, and translate complex analysis into clear, actionable recommendations for leaders. This role is ideal for a critical thinker and strong communicator who thrives in fast-moving environments—bringing structure to ambiguity, adapting quickly as priorities evolve, and driving alignment. You’ll also spot opportunities to modernize how we work by automating insights and innovating with advanced analytics, AI and machine learning.

Job summary

As a Quant Analytics, Senior Associate - Home Lending, you’ll source, integrate, and analyze data to uncover insights that drive measurable business value and improve the overall customer relationship. You’ll combine quantitative analysis with business context to explain performance, identify key drivers, and recommend actions that support growth—including strategies that encourage broader engagement across the firm. You’ll build and automate dashboards and reporting that make performance tracking easier and decision-making faster. You’ll partner across teams to deliver analytics solutions for complex business challenges and support strategic initiatives shaping the future of home lending.

Job responsibilities

• Partner with Sales, Marketing, Product, Finance, and Data & Analytics stakeholders to align on priorities and deliver data-driven solutions.


• Source and integrate data from multiple platforms to enable consistent, reliable performance measurement.


• Perform descriptive, diagnostic, and predictive analyses to identify trends, patterns, and actionable insights.


• Develop clear narratives that explain what happened, why it happened, and what actions to take next.


• Conduct deep-dive analyses to quantify drivers of performance and recommend actions to improve KPIs and relationship value.


• Build analytical frameworks that support complex business priorities and strategic initiatives.


• Design, automate, and maintain interactive dashboards for KPI tracking and stakeholder reporting.


• Identify opportunities to enhance business intelligence tooling and self-service reporting.


• Support strategic initiatives by translating analysis into clear, actionable recommendations for senior stakeholders.


• Collaborate on artificial intelligence and machine learning solutions to automate processes and develop new analytical capabilities.

Required qualifications, capabilities, and skills

• Bachelor’s degree in the fields above plus 4 years of relevant experience in an analytics-focused role (e.g., Data Scientist, Senior Analyst, Senior Engineer, or similar).


• Advanced SQL skills to query, transform, and validate data from multiple sources.


• Strong Python skills to automate workflows, support analytics, and enable repeatable reporting.


• Experience defining, tracking, and evaluating KPIs, including pre- and post-analysis to measure impact.


• Proficiency building and maintaining interactive dashboards and stakeholder-facing reporting.


• Ability to design and build end-to-end analytical tools and solutions.


• Demonstrated critical thinking and structured problem-solving skills for complex, ambiguous business questions.


• Strong collaboration and communication skills, including the ability to synthesize findings into actionable recommendations for senior stakeholders.


• Familiarity with cloud data platforms (e.g., AWS) and modern data warehouses (e.g., Snowflake), plus an understanding of large-scale data architecture.


• Ability to adapt quickly to changing priorities while maintaining high-quality analytical output.


• Successful use of generative AI prompting to accelerate analyses, improve consistency and quality of outputs, and support automation of repeatable workflows.

Preferred qualifications, capabilities, and skills

• Master’s degree in Information Systems, Computer Information Systems, Computer Science, Mathematics, Statistics, Engineering, Operations Research, or related field plus 2 years of relevant experience in an analytics-focused role (e.g., Data Scientist, Senior Analyst, Senior Engineer, or similar).


• Experience supporting analytics in home lending, consumer finance, or a related industry.