Compliance - Technology Operational Risk Management Director - Executive Di at JPMC Candidate Experience page

Plano, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Feb, 26

Salary

0.0

Posted On

21 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, AI Development, Software Development, Python, SQL, Data Integration, AI/ML Systems, Agentic AI, ML Ops, Cloud Platforms, Cybersecurity, Risk Management, Data Analysis, Technical Support, Automation

Industry

Financial Services

Description

Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class. As an Emerging Technology Operational Risk Director overseeing Applied Research Technology and Cybersecurity Operational Risk, you will focus on supporting Compliance, Conduct and Operational Risk (CCOR) in assessing Applied Research Technology and Cybersecurity Operational Risk. You will help build lightweight tools, data integrations, and automations that enable independent validation, evidence generation, and challenge first line of defense risk assessments. In addition, you will be responsible for directly supporting Applied Research risk reviews, while also enhancing broader operational risk processes such as risk identification, reporting, and risk data quality. You will bridge technical execution with risk oversight, strengthening regulatory credibility and ensuring scalable, data-driven assurance across the organization. You will be required to have strong software development skills, hands-on experience in data integration, and familiarity with AI/ML systems and pipelines, Agentic AI, ML Ops practices, and knowledge of cloud platforms. Job Responsibilities Work with data, architecture, and other resources towards independent validation of controls in areas such as AI/ML, Quantum Technologies, Cloud Computing and Networking, Immersive Technology (AR/VR). Collaborate with Risk, compliance, and audit teams to design, implement, and validate machine learning models supporting 2LOD reviews. Develop and leverage tooling to generate audit-ready evidence packs, risk metrics, and trend dashboards, reducing manual effort and improving the timeliness of oversight reporting. Analyze and interpret complex datasets to identify risk trends, control gaps, and emerging threats. Deliver technical support for risk reviews in areas including AI, cloud resilience, machine identity, and post-quantum cryptography by automating data gathering and analysis. Develop, test, and deploy AI-powered tools and agents to automate and enhance risk review processes. Standardize and automate data integration for KRIs, loss events, and control testing; provide scalable solutions that strengthen operational risk management. Build end-to-end machine learning pipelines, from data ingestion and preprocessing to model deployment and monitoring, leveraging ML Ops best practices for scalability and reliability. Provide technical guidance on best practices for model development, validation, governance, and ML Ops. Work closely with cross-functional teams, including IT, cyber operations, and business stakeholders. Present findings, recommendations, and technical solutions to both technical and non-technical audiences. Required qualifications, capabilities and skills Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field. 10+ years of experience in data science, machine learning, or AI development. Strong software development skills, with proficiency in Python and SQL. Hands-on experience in data integration and building scalable AI/ML systems and pipelines. Experience with Agentic AI and ML Ops practices. Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). Familiarity with cloud platforms (AWS, Azure, GCP). Excellent problem-solving, analytical, and communication skills. Preferred qualifications, capabilities and skills Experience in cyber operations, cybersecurity, or technical risk management.

Responsibilities

Oversee Applied Research Technology and Cybersecurity Operational Risk, focusing on compliance and operational risk assessments. Develop tools and automations to enhance risk management processes and support risk reviews.