Cybersecurity AI/ML Lead Data Scientist

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VA
Posted: 8 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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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

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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, engineer features, and develop statistical, machine learning, and deep learning models to support Cyber Operations. Your work involves identifying patterns, ensuring model interpretability, and building secure production code for analytics. You will utilize Python, SQL, Pandas, Scikit-Learn, PyTorch, and tools like Jupyter or SageMaker to solve security problems. The role requires applying knowledge of transformer architectures, generative AI, and large language models while maintaining auditability and safety standards. You will also manage data quality, monitor model drift, and integrate industry insights into security protocols within the financial services domain.

Skills

Python SQL Machine Learning Deep Learning Generative AI Transformer Architectures Scikit-Learn PyTorch Pandas Matplotlib Seaborn Plotly Jupyter AWS SageMaker CI/CD Feature Engineering Statistical Modeling Data Visualization

What you'll do

Perform 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.
Implement enterprise-authorized AI capabilities while ensuring human-in-the-loop validation and secure handling of sensitive data.
Establish portfolio-level guardrails for AI-assisted workflows to ensure traceability, auditability, and security standards.
Document model selection, interpretability, performance metrics, and limitations to support model governance.
Design, build, and maintain high-quality production code for analytical and machine learning solutions.
Apply industry insights and regulatory expectations to improve security control effectiveness and protocols.

What we're looking for

Obtain 5 plus years of experience with formal training or certification in security engineering concepts.
Proficiency in Python including Pandas, SQL, and 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 data cleaning, feature engineering, 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 SDLC, CI/CD practices, and secure software delivery.
Experience leading the safe use of enterprise-authorized AI capabilities and managing agentic workflows.