Workforce Planning - Data Scientist - Senior Associate

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.

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