Product Director - Data Product & Platform Solutions Engineering Lead

Ignite your passion for product innovation by leading customer-centric development, inspiring solutions, and shaping the future with your strategic vision and influence. Harness your technical expertise to transform client challenges into solutions that elevate their journey.

As a Product Director Data Product & Platform Solutions Engineering Lead  in firmwide Chief Data & Analytics Office Organization, you lead innovation through the development of products and features that delight customers. As a leader on the team, you leverage your advanced capabilities to challenge traditional approaches, remove barriers to success, and foster a culture of continuous innovation that helps inspire cross-functional teams create groundbreaking solutions that address customer needs. You will build a team of Solutions Engineers to advise firmwide teams in designing and integrating AI solutions within their application architecture.

Your role involves providing expert guidance and empowering clients to accelerate the delivery of AI value. With proficient communication and stakeholder management skills, you will cultivate excellent, collaborative relationships with Product, Engineering, and Architecture teams across JPMorgan Chase Lines of Business, Corporate Functions, and Internal Fusion Product and Engineering Teams to drive priority outcomes.

Job responsibilities

• Oversees the product roadmap, vision, development, execution, risk management, and business growth targets.
• Leads the entire product life cycle through planning, execution, and future development by continuously adapting, developing new products and methodologies, managing risks, and achieving business targets like cost, features, reusability, and reliability to support growth.
• Coaches and mentors, the product team on best practices, such as solution generation, market research, storyboarding, mind-mapping, prototyping methods, product adoption strategies, and product delivery, enabling them to effectively deliver on activities.
• Owns product performance and is accountable for investing in enhancements to achieve business objectives.
• Monitors market trends, conducts competitive analysis, and identifies opportunities for product differentiation.
• Lead and mentor a team of Solutions Engineer and data scientists, fostering innovation and collaboration.
• Provide technical expertise empowering our internal clients to design and deploy Machine Learning, Gen AI, and Agentic systems. Leverage your extensive ML experience to guide internal clients in their application development journey considering performance, evaluation, monitoring, resiliency and controls.
• Develop a deep understanding of firmwide standards for Model and Software Development Lifecycles and Information Security Controls.
• Anticipate risks associated with machine learning solutions and prediction/classification systems and strategize mitigation.  
• Foster a transparent cross-functional partnership with product management, engineering and client engagement and influence peers and team members to uphold these standards.

• Lead presentations, whiteboard sessions, and technical workshops, effectively communicating the value, differentiators and capabilities of our solutions. Communicate complex issues clearly and credibly to senior management and stakeholders.  

   

Required qualifications, capabilities, and skills

• 8+ years of experience or equivalent expertise delivering products, projects, or technology applications.
• Extensive knowledge of the product development life cycle, technical design, and data analytics
• Demonstrate ability to influence the adoption of key product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management.
• Experience driving change within organizations and managing stakeholders across multiple functions.
• Proficiency in programming languages such as Python, R, or Java, with a good emphasis on Python.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and industry leading GenAI models.
• Excellent skills in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
• Experience in developing, training, and deploying machine learning models, Gen AI models and including knowledge of model evaluation and optimization techniques.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
• Experience with big data technologies like Hadoop, Spark, or Apache Kafka for handling large datasets.