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.
As a Product Manager within the 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. As a core member of the team, 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 data discovery, analytics and data intake to build customer journeys with Omni Channel Personalization focus and to support next-best-action capabilities across mobile, web, contact center, branch, and marketing. You will translate research and analytics into clear roadmaps, partner with data science, machine learning engineering, channel teams, and business stakeholders to prioritize opportunities, design and iterate recommendation, next-best-action, and agentic solutions, run experiments to validate impact, and operationalize scalable, reliable model lifecycle infrastructure—while upholding privacy, consent, and fairness standards.
Job responsibilities
- Develops a product strategy and product vision that delivers value to customers
- Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap
- Lead discovery efforts, conducting research with data sources and translating findings into well-defined roadmaps.
- Builds the framework and tracks the product's key success metrics such as cost, feature and functionality, risk posture, and reliability
- 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 Owners as well as partner product stakeholders for data discovery and LLM/ML‑based solutions
- Champion data governance, lineage, quality, auditability, and Explainability across all data and artificial intelligence-driven decisions
- Uphold responsible AI and data practices in partnership with risk, privacy, and compliance teams, including consent management, and fairness.
Required qualifications, capabilities, and skills
- 8+ years of experience or equivalent expertise in product management, data analytics or a relevant domain area
- Advanced knowledge of the product development life cycle, design, and data analytics
- Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management
- Strong expertise in large-scale structured query language, event-based data, streaming concepts, dimensional modeling, and operational data design
- Excellent 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
- Strong understanding of data governance, lineage, quality, controls, and audit requirements in a regulated environment
- Excellent stakeholder management: ability to align cross-functional teams (Audiences, Insights, Channels, Marketing, Analytics) and drive decisions independently without escalation
- Excellent communication skills, with the ability to translate complex data and intelligence concepts into clear business outcomes
Preferred qualifications, capabilities, and skills
- Demonstrated prior experience working in a highly matrixed, complex organization
- Experience with AI-driven or agentic product experiences, personalization engines.
- Experience in Data Analytics and building trusted data foundations for executive reporting, auditability, and cross-business performance measurement
- Experience running A/B Testing, experimentations