Personalization Product Director – Data Platform Lead
You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with clients. You will drive the strategy and execution of ML‑powered personalization and next‑best‑action capabilities for marketing and servicing across mobile, web, contact center, branch, and marketing channels. You will translate research and analytics into clear roadmaps, partner with Engineers and Data Scientists to design and iterate Product Features, run experiments to validate impact, and deliver measurable outcomes while upholding privacy, consent, and fairness standards.
As a Product Director in Personalization & Customer Insights Team, you are an integral part of the team that innovates new product offerings and leads the end-to-end product life cycle. We are hiring a leader to shape the newly formed Personalization Data Platform team. As a core leader, you are responsible for acting as the voice of the customer and developing profitable products that provide customer value. Utilizing your deep understanding of how to get a product off the ground, you guide the successful launch of products, gather crucial feedback, and ensure top-tier client experiences. With a strong commitment to scalability, resiliency, and stability, you collaborate closely with cross-functional teams to deliver high-quality products that exceed customer expectations. You will lead the data products and integrations that feed the operating memory for our agentic channel.
Your team curates secure, consented customer context and personalized signals that help the assistant understand intent and maintain continuity—delivered to the Channel/Interface team and to domain agents that take action on customers’ behalf. Lead the data products that power the operating memory for our new Chase agentic channel—curating secure, consented customer context and personalized signals—while partnering with the Channel/Interface team and domain agents. Also drive ML‑powered personalization and next‑best‑action optimization across channels for marketing and servicing.
- 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 objectives
- 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 the development of ML‑powered personalization and next‑best‑action capabilities for marketing and servicing; frame hypotheses, prioritize use cases, and measure impact through experimentation.
- Translate user research and analytics into epics, user stories, and acceptance criteria; manage the product backlog and delivery across discovery, launch, and continuous improvement.
- Collaborate closely with Data Scientists and Engineers across the product lifecycle (design, training, evaluation, deployment, monitoring) for personalization solutions.
- Champion an API‑ and event‑driven architecture on cloud infrastructure to ensure scalable, reliable delivery of context and signals across channels. Establish and track product KPIs for engagement, quality, and business outcomes; ensure delivery against time, cost, and quality targets.
- Uphold responsible data practices in partnership with risk, privacy, and compliance teams, including consent management, and fairness. Provide people leadership: mentor product managers, foster a culture of experimentation and measurable outcomes, and influence cross‑functional partners
- 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
- Proven 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
- Proven product management leadership delivering AI‑powered products to production in customer‑facing environments, in close partnership with Data Scientists and ML Engineers across the model lifecycle.
- Experience defining and shipping data products that support agentic assistants (e.g., operating memory, context, or signals) and integrating them with partner teams that own the channel experience.
- Demonstrated success with ML‑driven personalization and next‑best‑action for marketing and/or servicing, including experimentation (e.g., A/B testing) and outcome measurement.
- Proficient knowledge of the product development life cycle, including discovery, requirements definition, and backlog management (epics, user stories, refinement, PBR, JIRA).
- Strong data literacy and the ability to turn user research, journey insights, and product metrics into decisions and roadmaps that deliver on time, cost, and quality.
- Excellent people leadership and stakeholder management: mentoring product managers and influencing partners across Product, Design, Engineering, Marketing/Servicing, and business teams.
- Experience with API‑first delivery on cloud (e.g., AWS) and coordination across multi‑channel experiences (mobile, web, contact center, branch, marketing). Clear, structured communicator with strong written and presentation skills
- Recognized thought leader within a related field
- Demonstrated prior experience working in a highly matrixed, complex organization
- Hands‑on experience with Personalization and Recommendation systems in production
- Experience with conversational/agentic systems, operating‑memory or context architectures, and recommendation systems for marketing/servicing.
- Degree in Engineering, Data Science, Business, or a comparable field of study.
- Knowledge of current digital banking trends and customer experience patterns, and familiarity with privacy, consent, and fairness considerations in AI.