Data Scientist, Sr. Associate

JP Morgan Chase; Plano (TX); On-site; USD 110,000 - 140,000; Full time

Job summary

JP Morgan Chase is seeking an experienced Data Scientist on the Home Lending Data & Analytics team in Plano, TX. You will drive campaign performance through rigorous measurement and data-driven insights, partnering with Marketing to optimize origins and messaging.

Responsibilities include identifying trends, analyzing A/B tests, and translating results into actionable recommendations. You will leverage GenAI/LLM-assisted workflows to speed hypothesis generation and insights while ensuring sound

Qualifications

• Strong SQL skills and ability to merge data from multiple sources.
• Experience with Python or other analytics tools and Excel.
• 3+ years in business/marketing analytics or similar.
• Familiarity with GenAI/LLM tools to accelerate analysis.

Responsibilities

• Identify trends and insights to improve campaign performance.
• Plan and analyze A/B tests and experiments for marketing lift.
• Collaborate with analytics and marketing to implement outputs in campaigns.
• Create stakeholder-ready deliverables with transparent methods.

Skills

SQL

Python

Excel

Data analysis

Communication

GenAI/LLM

Tools

SAS

R

Alteryx

Job description

This is an experienced Data Scientist position on the Home Lending Data & Analytics team supporting Originations, partnering primarily with Marketing to drive campaign performance through rigorous measurement, data-driven insights, and continuous optimization. You will combine strategy, business analysis, and data skills to identify meaningful trends, uncover opportunities, and tell the full story behind performance (including what didn’t work), enabling objective decision‑making. You will also leverage modern analytics techniques, including responsible use of GenAI/LLM tools, to accelerate analysis, expand exploration breadth, and improve the efficiency of insight generation while staying accountable for decisions and conclusions.

Key responsibilities

• Proactively identify and communicate meaningful trends, patterns, and actionable insights to stakeholders across campaign performance, funnel conversion, lead quality, and outreach effectiveness.
• Support marketing targeting and lift measurement, including planning and analyzing A/B tests and other experiments; quantify incremental impact and translate results into clear recommendations.
• Partner with cross‑functional teams to implement predictive analytics outputs (built by a separate modeling team) into targeted marketing campaigns; understand model intent, inputs, and limitations well enough to apply appropriately and interpret results.
• Use data discovery to “turn over more stones” and uncover drivers of performance, leveraging GenAI/LLM‑assisted workflows to speed hypothesis generation, summarization, and exploratory analysis while validating findings with data and sound measurement practices.
• Source and merge data from platforms (e.g., campaign data, digital funnel, lead/outreach datasets) to build a cohesive narrative of what happened and what to do next.
• Collaborate with sales strategy analytics and other partners to pilot programs, measure effectiveness, and support transition into production processes when pilots are successful.
• Create clear, stakeholder‑ready deliverables (reads, decks, dashboards/outputs) that are transparent about assumptions, methodology, and trade‑offs; avoid cherry‑picking by presenting balanced insights and limitations.

Qualifications

• Strong ability to analyze problems, dig deep into data, understand “why,” design solutions, and communicate confidently (verbal and written) with relevant stakeholders to gain buy‑in.
• Strong SQL skills, including merging data from multiple sources.
• Experience with Python (preferred) or another analytics tool/language (e.g., SAS, R, Alteryx). Strong Microsoft Excel skills.
• 3+ years of experience in business analysis, marketing analytics, or a similar role supporting campaign measurement and optimization.
• Practical familiarity with how predictive models are used in marketing (you do not need to build models, but should be able to work with model outputs, assumptions, and limitations).
• Comfort using GenAI/LLM tools to improve analytical efficiency (e.g., accelerating exploration and drafting insights), paired with strong judgment, validation discipline, and ownership of final conclusions.
• Mortgage banking experience and/or experience with Marketing/CRM data is a plus.