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 production code for scalable, auditable solutions. You will utilize Python, SQL, Pandas, Scikit-Learn, PyTorch, and tools like Jupyter, SageMaker, and VS Code. The role requires applying transformer architectures, generative AI, and large language models to security use cases. You must ensure model governance, interpretability, and traceability while navigating financial services IT systems and security telemetry.
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.
Design, build, review, debug, 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 standards.
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 statistical distributions applied to cybersecurity or technology risk.
Demonstrate advanced Python skills including Pandas, SQL, and visualization tools like Matplotlib, Seaborn, or Plotly.
Experience leading teams in the safe use of enterprise-authorized AI capabilities for security engineering workflows.
Experience preparing complex datasets for modeling, including data cleaning, feature engineering, and data quality assessment.
Proficiency with Software Development Life Cycle, CI/CD practices, application resiliency, and secure software delivery.
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).
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