Pay
$118K–$195K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,817 postings in the last year. Stated ranges, not salaries paid.
ChaseNet Data Scientist
Plano, TX, United States
Actively hiring, first seen by us 5 days ago- Pay
- Pay not listedSimilar roles state $118K–$195K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingManage, transform and analyze large payments datasets for pricing and profitability work
Build recurring and ad-hoc reporting on ChaseNet performance and merchant economics
Develop models to evaluate pricing scenarios, interchange impacts and repricing opportunities
Write SQL and Python code to extract and process data from payments platforms
Turn business questions from product, pricing and finance teams into clear recommendations
From the employer’s posting
Manage, transform, and analyze large payments datasets to support ChaseNet pricing, profitability, and portfolio optimization initiatives.
Design, build, and maintain recurring and ad-hoc reporting that provides visibility into ChaseNet performance, revenue drivers, and merchant economics.
Develop analytical frameworks and models to evaluate pricing scenarios, interchange impacts, repricing opportunities, and merchant business cases.
Write efficient, well-documented SQL and Python code to extract, process, and analyze data from large-scale payments platforms.
Partner with product, pricing, finance, and relationship management teams to translate business questions into structured analyses and clear recommendations.
About JPMorgan Chase
ChaseNet is JPMorganChase's proprietary closed-loop payments network that connects Chase-issued cardholders directly with merchants acquired by Chase Merchant Services.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 5, 20265 days ago
- Recorded sightings
- 7
- Last seen by us
- Nov 11, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 5
Early. Similar jobs usually come down between day 8 and day 59.
At JPMorgan Chase, jobs usually come down by about day 15.
From 11,367 similar postings that came down, and 967 of JPMorgan Chase’s. Coming down is not always a hire.
JPMorgan Chase is hiring
366 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Scientist hiring has slowed
- Takes jobs down at a usual pace
- 3% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- Tableau
Where the posting names them
- Partner with product, pricing, finance, and relationship management teams to translate business questions into structured analyses and clear recommendations. - Write efficient, well-documented SQL and Python code to extract, process, and analyze data from large-scale payments platforms. - Support governance, quality control, and process improvement across analytics workflows, including automation and documentation.
- Undergraduate degree with 3+ years of experience - Understanding of SQL-based coding and Python. - Consulting orientation with the ability to influence both internal and external business partners.
Partner with product, pricing, finance, and relationship management teams to translate business questions into structured analyses and clear recommendations. Write efficient, well-documented SQL and Python code to extract, process, and analyze data from large-scale payments platforms. Support governance, quality control, and process improvement across analytics workflows, including automation and documentation.
Undergraduate degree required; MBA preferred. Understanding of SQL-based coding and Python. Consulting orientation with the ability to influence both internal and external business partners.
- Proven experience working in large teams in an advanced analytical environment. - Proven experience with emerging technologies related to insights and the ability to do rapid prototyping (in Tableau). - Ability to synthesize data sets into streamlined, clear, and actionable messages.
Proven experience working in large teams in an advanced analytical environment. Proven experience with emerging technologies related to insights and the ability to do rapid prototyping (in Tableau). Ability to synthesize data sets into streamlined, clear, and actionable messages.
Your next step
Complete your application on jpmc.fa.oraclecloud.com. The employer’s form will show what is required.
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Already applied? Track this application
About JPMorgan Chase
- People
- About 318,512 in 2025.Annual report (SEC Form 10-K)
- Company
- Listed as JPM.
- Layoff notices
- Notices this year and last cover 152 people. The latest was filed March 23, 2026.State WARN notices
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 6% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
About ChaseNet
ChaseNet is JPMorganChase's proprietary closed-loop payments network that connects Chase-issued cardholders directly with merchants acquired by Chase Merchant Services. By routing eligible transactions through a single Chase-owned rail rather than the traditional open-loop network, ChaseNet simplifies the economics of card acceptance, enables customized pricing constructs, and delivers richer transaction data to both merchants and the firm. ChaseNet supports some of the largest merchants in the United States and plays a central role in Chase's merchant services growth strategy.
As a ChaseNet Data Scientist, Associate in the ChaseNet Analytics team, you will work with large and complex payments datasets to generate insights that inform pricing strategy, merchant profitability, portfolio performance, and strategic decision-making.
Job Responsibilities
- Manage, transform, and analyze large payments datasets to support ChaseNet pricing, profitability, and portfolio optimization initiatives.
- Design, build, and maintain recurring and ad-hoc reporting that provides visibility into ChaseNet performance, revenue drivers, and merchant economics.
- Develop analytical frameworks and models to evaluate pricing scenarios, interchange impacts, repricing opportunities, and merchant business cases.
- Partner with product, pricing, finance, and relationship management teams to translate business questions into structured analyses and clear recommendations.
- Write efficient, well-documented SQL and Python code to extract, process, and analyze data from large-scale payments platforms.
- Support governance, quality control, and process improvement across analytics workflows, including automation and documentation.
- Communicate findings clearly to both technical and non-technical audiences through written narratives, visualizations, and presentations.
- Contribute to innovation initiatives, including the use of AI and emerging technologies to improve analytical capabilities and decision support.
Required qualifications, capabilities, and skills:
- Undergraduate degree with 3+ years of experience
- Understanding of SQL-based coding and Python.
- Consulting orientation with the ability to influence both internal and external business partners.
- Understanding of the payments value chain, including merchants, brands, acquirers, networks, and issuers.
- Proven experience working in large teams in an advanced analytical environment.
- Proven experience with emerging technologies related to insights and the ability to do rapid prototyping (in Tableau).
- Ability to synthesize data sets into streamlined, clear, and actionable messages.
- Experience creating business initiatives and communicating ideas with a digitally focused and data-driven mindset.
- Proven ability to develop relationships with a wide array of partners, executives, and customers.
Preferred qualifications, capabilities, and skills:
- AI/ML and automation skills, AI/ML solutions creation, and software engineering skills preferred.
- Experience in the payments industry and/or technology-enabled industries (preferred but not required).
- Working knowledge of the credit card value chain, including the roles of issuers, acquirers, networks, processors, and merchants.
- Familiarity with network fees and interchange economics, including how interchange categories, assessments, and network-level fees are structured.
- Familiarity with processing fees and merchant pricing constructs such as interchange-plus, blended pricing, and tiered pricing.
Manage, transform, and analyze large payments datasets to support ChaseNet pricing, profitability, and portfolio optimization initiatives.
Design, build, and maintain recurring and ad-hoc reporting that provides visibility into ChaseNet performance, revenue drivers, and merchant economics.
Develop analytical frameworks and models to evaluate pricing scenarios, interchange impacts, repricing opportunities, and merchant business cases.
Partner with product, pricing, finance, and relationship management teams to translate business questions into structured analyses and clear recommendations.
Write efficient, well-documented SQL and Python code to extract, process, and analyze data from large-scale payments platforms.
Support governance, quality control, and process improvement across analytics workflows, including automation and documentation.
Communicate findings clearly to both technical and non-technical audiences through written narratives, visualizations, and presentations.
Contribute to innovation initiatives, including the use of AI and emerging technologies to improve analytical capabilities and decision support.
Experience Requirements
Undergraduate degree required; MBA preferred.
Understanding of SQL-based coding and Python.
Consulting orientation with the ability to influence both internal and external business partners.
3+ years of experience in the payments industry and/or technology-enabled industries (preferred but not required).
Understanding of the payments value chain, including merchants, brands, acquirers, networks, and issuers (preferred but not required).
Proven experience working in large teams in an advanced analytical environment.
Proven experience with emerging technologies related to insights and the ability to do rapid prototyping (in Tableau).
Ability to synthesize data sets into streamlined, clear, and actionable messages.
Experience creating business initiatives and communicating ideas with a digitally focused and data-driven mindset.
Proven ability to develop relationships with a wide array of partners, executives, and customers.
Preferred Knowledge
AI/ML and automation skills, AI/ML solutions creation, and software engineering skills preferred.
Working knowledge of the credit card value chain, including the roles of issuers, acquirers, networks, processors, and merchants.
Familiarity with network fees and interchange economics, including how interchange categories, assessments, and network-level fees are structured.
Familiarity with processing fees and merchant pricing constructs such as interchange-plus, blended pricing, and tiered pricing.
Exposure to ChaseNet or other closed-loop or on-us payment constructs.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Plano, TX, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.