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Data Scientist, Senior Associate

Pay
Pay not listedSimilar roles state $118K–$193K
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 posting
  • Identify and communicate trends and actionable insights on campaigns, funnel conversion and lead quality

  • Plan and analyze A/B tests and experiments to quantify incremental impact

  • Apply predictive model outputs to targeted marketing campaigns

  • Source and merge campaign, digital funnel and lead data into one performance story

  • Produce stakeholder-ready decks, reports and dashboards with stated assumptions and limitations

From the employer’s posting
Proactively identify and communicate meaningful trends, patterns, and actionable insights to stakeholders
planning and analyzing A/B tests and other experiments; quantify incremental impact
Partner with cross-functional teams to implement predictive analytics outputs
Source and merge data from platforms (e.g., campaign data, digital funnel, lead/outreach datasets)
Create clear, stakeholder-ready deliverables (reads, decks, dashboards/outputs)

What you’ll bring

All qualifications

Core experience

  • 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).
  • 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).
Qualification wording
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).
Apply at JPMorgan Chase

Posting record

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Actively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 30, 20264 days ago
Recorded sightings
5
Last seen by us
Nov 3, 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

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 4

Early. Similar jobs usually come down between day 7 and day 55.

From 9,971 similar postings that came down. Coming down is not always a hire.

JPMorgan Chase is hiring

413 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring is steady
  • Takes jobs down at a usual pace
  • 3% of open jobs were reposted
Hiring record

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
  • R
  • SAS
  • SQL
  • Excel
Where the posting names them
- 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.
- 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.

Your next step

Complete your application on jpmc.fa.oraclecloud.com. The employer’s form will show what is required.

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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

View original posting ↗

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.
Source details

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Location & working pattern

Plano, TX, United States

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