The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s AI and data journey. This includes developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As an Product Manager Model Development - Vice President within the Chief Data & Analytics Office (CDAO), you will have the unique opportunity to be a critical player in our firm-wide efforts in coordinating and building products that enable Data Scientists at the firm to build and deploy their AI models. You will work closely with cross-functional teams to deliver best-in-class products for the firm.

 

Job Responsibilities 

Define a strategic vision and roadmap for the product that includes milestones, deliverables, resources, and timelines 

Build a streamlined experience for AI and GenAI models, with built-in policy enforcement to ensure governance and controls across the model lifecycle

Work with stakeholders across the various businesses (Investment Bank, Consumer Bank, etc.) and functional groups (Legal, Technology, Controls) to collect business requirements, create PRDs, and ship high quality products that solve business needs 

Drive the development of products for streamlining the passage of models through the Model Development Lifecycle, with the objective of reducing the time to market for a machine learning model

 

Required qualifications, capabilities and skills

6+ years of experience in product management with proven ability to lead and develop high performing product teams

Proven delivery of enterprise scale products 

Excellent leadership and collaboration skills, with the ability to positively influence and inspire technology teams and stakeholders 

Strong agile mindset, able to iterate fast and give early feedback 

Strong track record of owning and developing a product domain strategy and roadmap

Able to balance short-term goals and long-term vision in highly complex environments

Expertise on the AI lifecycle, spanning from data discovery, data processing, model development, model deployment, and model monitoring 

Expertise in Cloud computing and architectures

 
Preferred qualifications, capabilities, and skills

Demonstrated prior experience working in a highly matrixed, complex organization