Senior Data Scientist - Marketing Analytics & GenAI

JPMorganChase; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

On-site health center

Retirement savings plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Job summary

Chase is seeking an experienced Data Scientist for the Home Lending Data & Analytics team. You will drive campaign performance through measurement, data-driven insights, and optimization, partnering with Marketing to inform decisions and scale insights using GenAI/LLM tooling thoughtfully.

You will work with data across campaigns, funnel, and leads to tell the full story, including what didn’t work, and translate findings into actionable recommendations for stakeholders and production teams

Qualifications

• 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.

Responsibilities

• Identify trends, patterns, and actionable insights across campaign performance, funnel conversion, lead quality, and outreach effectiveness.
• Plan and analyze A/B tests and other experiments; quantify incremental impact and translate results into clear recommendations.
• Collaborate with cross-functional teams to implement predictive analytics outputs into targeted marketing campaigns; interpret model inputs and limitations.

Skills

SQL

Python

Excel

Communication

Problem solving

Tools

SAS

R

Alteryx

Job description

Chase is seeking an experienced Data Scientist for the Home Lending Data & Analytics team. You will drive campaign performance through measurement, data-driven insights, and optimization, partnering with Marketing to inform decisions and scale insights using GenAI/LLM tooling thoughtfully.

You will work with data across campaigns, funnel, and leads to tell the full story, including what didn’t work, and translate findings into actionable recommendations for stakeholders and production teams