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Workforce Planning - Data Scientist - Senior Associate

Wilmington, DE, United States

Actively hiring, first seen by us today
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

Before you apply

Work authorization
Must already have the right to workThis role is not eligible for visa sponsorship
Education & alternatives
Required Qualifications, Capabilities, and Skills - Master’s Degree with 3+ years or Doctorate (PhD) with 1+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines. - Experience supporting AI/ML projects with multiple team members.
Apply at JPMorgan Chase

Posting record

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

Status in our records
Live
First seen by us
Nov 4, 2026today
Recorded sightings
1

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 0

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

At JPMorgan Chase, jobs usually come down by about day 14.

From 10,040 similar postings that came down, and 903 of JPMorgan Chase’s. Coming down is not always a hire.

JPMorgan Chase is hiring

421 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

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  • Python
  • R
  • Scala
  • SQL
  • AWS
  • Azure
  • GCP
  • Hadoop
  • Hive
  • Spark
Where the posting names them
- Foundational understanding of the math and theory behind AI/ML algorithms, with the ability to reason about model assumptions, behavior, and limitations beyond empirical validation. - Proficient in data science programming languages like Python, R or Scala. - Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
- Proficient in data science programming languages like Python, R or Scala. - Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.). - Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence.
- Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills. - Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP). - Previous experience leading highly complex cross-functional technical projects with multiple stakeholders.

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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 ↗

If you like turning real-world problems into models that actually move the needle, you’ll fit right in. Our Workforce Planning (WFP) Data Science team builds AI/ML solutions that help forecast demand, optimize capacity, and sharpen scheduling—at the scale of Chase call centers, back office operations, and ~5,200 branches. The work is complex, high-impact, and rarely “plug-and-play”—you’ll frame the problem, choose the right math, and deliver solutions built for action. If real-time decisioning sounds like your kind of challenge, this is where you belong.

As a Data Scientist Associate Senior within the Consumer and Community Banking in Workforce Planning (WFP) you will solve complex, data-intensive, and often unstructured business problems that materially impact operations. You will independently frame ambiguous questions, translate them into mathematical formulations, and select modeling approaches grounded in strong theoretical fit—not just benchmark off-the-shelf algorithms. You will design, develop, and productionize rigorous AI/ML solutions that advance next-generation capabilities, including moving toward real-time inference and decision-making across Workforce Planning.

Job Responsibilities

  • Design and development of Machine Learning, Artificial Intelligence and Statistical models. 
  • Support AI/ML projects individually or part of a project team.
  • Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
  • Select and apply the appropriate modeling approach based on principled understanding of the problem structure and underlying assumptions, while staying up to data on the latest AI/ML research.
  • Ensure the robustness of any data science solution.
  • Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
  • Work effectively and gain credibility and respect of others including peers, clients and other stakeholders.

 

Required Qualifications, Capabilities, and Skills

  • Master’s Degree with 3+ years or Doctorate (PhD) with 1+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
  • Experience supporting AI/ML projects with multiple team members.
  • Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
  • Foundational understanding of the math and theory behind AI/ML algorithms, with the ability to reason about model assumptions, behavior, and limitations beyond empirical validation.
  • Proficient in data science programming languages like Python, R or Scala.
  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
  • Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence. 

 

Preferred Qualifications, Capabilities, and Skills

  • Advanced expertise with Time Series and Operations Research techniques. 
  • Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
  • Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
  • Previous experience leading highly complex cross-functional technical projects with multiple stakeholders. 

 

 This role is not eligible for visa sponsorship.  This role is 5 days a week full time in office.

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Pay

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Location & working pattern

Wilmington, DE, United States

Working pattern and location restrictions need checking in the full posting.

Work authorization
- Previous experience leading highly complex cross-functional technical projects with multiple stakeholders. This role is not eligible for visa sponsorship. This role is 5 days a week full time in office.

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