below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$160,000–$235,812.
Based on 240 similar postings.
Employer
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
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
As a Cybersecurity AI/ML Lead - Data Scientist within the Cybersecurity & Technology Controls team, you will develop advanced analytical and machine learning solutions to address complex cybersecurity and technology risk challenges. You will perform exploratory data analysis, statistical modeling, and deep learning to solve security problems, preparing model-ready datasets through feature engineering and data quality assessments. Your daily work involves designing, building, and maintaining secure production code while establishing portfolio-level guardrails for AI-assisted workflows. You will utilize Python, SQL, Pandas, Scikit-Learn, and PyTorch, alongside tools like Jupyter, SageMaker, and VS Code. The role requires applying these skills to financial services IT systems, focusing on model interpretability, CI/CD practices, and the application of transformer architectures and generative AI for applied security use cases.
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 cleaning, and quality assessments.
Design, build, and maintain secure production code for analytical and machine learning solutions.
Establish portfolio-level guardrails for AI-assisted workflows to ensure traceability, auditability, and security.
Document model selection, interpretability, performance metrics, and limitations to support model governance.
Apply industry insights and regulatory expectations to improve security processes and control effectiveness.
What we're looking for
Obtain 5 plus years of experience with formal training or certification in security engineering concepts.
Possess working knowledge of probability, statistics, and their application to cybersecurity or technology risk use cases.
Demonstrate advanced Python skills including Pandas, SQL, and data visualization tools like Matplotlib, Seaborn, or Plotly.
Experience leading teams in the safe use of enterprise-authorized AI capabilities for security engineering workflows.
Experience using notebooks such as Jupyter, SageMaker, or VS Code to analyze data and communicate results.
Possess working knowledge of Scikit-Learn and machine learning or deep learning frameworks such as PyTorch.
Demonstrate proficiency with Software Development Life Cycle, CI/CD practices, application resiliency, and secure software delivery.
Possess in-depth knowledge of the financial services industry and related IT systems.
Bachelor’s degree in Data Science, Mathematics, Statistics, Econometrics, Computer Science, or a related field, plus 3+ years of applied data science experience (preferred).
Experience with TCP/IP networking, cybersecurity technologies, and security-related telemetry (preferred).
Experience monitoring models in production and identifying data quality, drift, or performance issues (preferred).
Experience deploying statistical or machine learning models in production environments, including AWS SageMaker (preferred).
Working knowledge of Large Language Models, natural language models, vector embeddings, and responsible AI practices (preferred).
AI
Machine Learning
Python
Agentic AI
Model Training
Post-training
Vulnerability Research
Malware Analysis
Program Analysis
Software Security
Intrusion Detection
Large-scale Data Systems
Systems Software
Security Tooling
Accelerated Computing