Compliance - Product Manager Data Science (Risk Management) - Executive Director

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 a Product Manager in the Compliance Conduct and Operational Risk (CCOR) Data Analytics division, you will play a pivotal role in ensuring the seamless execution of various projects and initiatives across diverse domains. You'll be at the forefront of innovation, crafting project and rollout plans for initiatives that involve model development in collaboration with CCOR SMEs, Product Leads, Model Risk Management, Technology, and others.  Your expertise will guide the data science team, ensuring they meet agreed milestones while proactively addressing any delays and collaborating with stakeholders to keep projects on track. You'll facilitate smooth interactions with business partners, aligning on business requirements and objectives, and nurturing strong relationships.  

Your role will also involve close collaboration with model review, control, legal, and compliance teams to ensure adherence to all regulatory and compliance requirements.  You will prepare and present reports on project progress and outcomes to senior managers, ensuring clear communication of project requirements and updates to all relevant parties.  Additionally, you will be responsible for leading initiatives to enhance team satisfaction, foster a positive work environment, and provide opportunities for professional development.  In this role, you will have the opportunity to drive the delivery of innovative AI/ML solutions across Compliance, Conduct and Operational Risk through modern architecture & engineering practices.

Job Responsibilities

• Develop and execute the AL/ML capabilities and product vision developed with CCOR product managers and risk SMEs. 
• Oversee the data science teams progress with respect to the agreed project plan to ensure timely delivery. 
• Proactively address any delays and collaborate with stakeholders to keep projects on track.
• Facilitate smooth interactions with business and technology partners, addressing and anticipating any issues and maintaining strong relationships. Collaborate with partners to ensure alignment on business requirements and objectives. 
• Demonstrated ability to lead and manage the implementation of AI/ML models in technology stack, issue resolution, and roll out. 
• Accustomed to working with JIRA, User Stories, etc.
• Work closely with model review, control, legal, and compliance teams to ensure adherence to all necessary requirements. 
• Address any control/compliance-related concerns to ensure our work meets required standards.
• Prepare and present reports on project progress and outcomes to senior managers. 
• Ensure clear communication of project requirements and updates to all relevant parties.

• Implement initiatives to improve team satisfaction and foster a positive work environment. 

Required qualifications, capabilities, and skills

• Proven experience in product management, with a track record of successfully managing processes and controls to deliver projects on time.
• Strong collaboration skills with the ability to build and maintain relationships with business partners and stakeholders, especially technology.
• Experience in regulatory and compliance coordination, with a strong understanding of necessary requirements.
• Excellent communication and reporting skills, with the ability to present complex information clearly to senior managers.
• Undergraduate degree in Engineering, Computer Science, Physical Sciences, Econometrics, Business, Statistics, or other any quantitative discipline.
• Experience in managing or working with large scale technology transformation projects involving analytics.
• Core knowledge in data science and machine learning, including modeling fundamentals and a strong grounding in statistics and probability. Understanding of various data analytics, AI/ML, LLM, Gen AI, and ML techniques. Demonstrated experience in Python and/or R or any other and understanding of libraries/frameworks (eg Pandas, NumPy, scikit-learn, PyTorch, etc.).
• Reproducibility - Best practices for notebooks, code packaging, and experiment tracking (MLflow, Weights & Biases)
• MLOps - Experience in Monitoring & Maintenance strategies (Drift detection, retraining strategies); Good understanding in model deployment pipelines;
• Experience in data engineering best practices, including data warehouses, data lakes, modern data stack tools and microservice API integration; Hands-on professional experience in software development especially with analytical & computationally intensive systems, digital transformations leveraging cloud technologies (AWS, GCP, Azure, Databricks etc.). 
• Experience in working with model review, control, legal, and compliance teams.

Preferred qualifications, capabilities, and skills

• Ability to independently address control/compliance-related concerns.
• Strong problem-solving skills and the ability to proactively address project delays.
• Strong multitasking skills and the ability to manage multiple initiatives across different domains.
• Post graduate degree is preferred
• Working knowledge of C/C#/C++ or others is a plus
• Experience in financial services industry especially in Operational Risk Management, Anti-Money Laundering & Know Your Customer, Trade Surveillance model development
• Experience with EKS or AKS provisioning is a plus