Cybersecurity AI/ML Lead Data Scientist

JPMorgan Chase

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
McLean, VA
Posted
8 days ago
Freshness
Confirmed live 2 days ago

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How this pay compares to similar roles

Similar $203k
$152k most similar roles pay here $251k

This listing doesn't post a salary. Most similar roles pay $163,725–$241,750.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Cybersecurity AI/ML Lead Data Scientist

As a Cybersecurity AI/ML Lead - Data Scientist within the Cybersecurity & Technology Controls team, you will serve as a core technical contributor developing advanced analytical and machine learning solutions to address complex cybersecurity and technology risk challenges. You will perform exploratory data analysis on security datasets, conduct statistical modeling, and develop deep learning models to support Cyber Operations teams. Your daily work involves preparing model-ready data through feature engineering, designing secure production code, and establishing guardrails for AI-assisted workflows. You will utilize Python, SQL, Pandas, Scikit-Learn, PyTorch, and tools like Jupyter or SageMaker to build scalable solutions. The role requires applying knowledge of transformer architectures, generative AI, and large language models to solve security problems while ensuring model interpretability, auditability, and compliance with financial services industry standards and regulatory expectations.

What you'll do

  • Conduct exploratory data analysis on security datasets to identify patterns and communicate findings to stakeholders.
  • Develop and evaluate statistical, machine learning, and deep learning models for cybersecurity use cases.
  • Prepare model-ready datasets through feature engineering, data quality assessment, and cleaning techniques.
  • Design, build, and maintain secure production code for analytical and machine learning solutions.
  • Establish guardrails for AI-assisted workflows to ensure traceability, auditability, and security standards.
  • Document model governance including selection, interpretability, performance metrics, and limitations.
  • Integrate enterprise-authorized AI capabilities into data architecture and model analysis workflows.
  • Apply industry insights and regulatory expectations to improve security control effectiveness.

What we're looking for

  • Obtain 5 plus years of experience with formal training or certification in security engineering concepts.
  • Proficiency in advanced Python including Pandas, SQL, and data visualization tools like Matplotlib, Seaborn, or Plotly.
  • Working knowledge of Scikit-Learn for modeling and deep learning frameworks such as PyTorch.
  • Experience preparing complex datasets through feature engineering, data cleaning, and quality assessment.
  • Knowledge of probability, statistics, and their application to cybersecurity or technology risk use cases.
  • Ability to communicate model selection, interpretability, performance metrics, and limitations to technical and business stakeholders.
  • Proficiency with Software Development Life Cycle (SDLC), CI/CD practices, and secure software delivery.
  • In-depth knowledge of the financial services industry and related IT systems.

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