Responsibilities
- Collaborate with Product Managers to shape and communicate a strategic product roadmap that supports business goals.
- Maintain and prioritize a clear, well-structured product backlog with detailed user stories and acceptance criteria.
- Develop thorough user stories and analyze requirements to convert complex business needs into actionable development tasks.
- Establish sprint objectives and work with development teams during planning to ensure shared understanding of deliverables.
- Map user journeys and conduct usability testing to uncover customer needs and validate product choices with data.
- Review and formally accept completed work, verifying it meets defined quality standards and acceptance conditions.
- Coordinate across teams, tracking progress and communicating delivery forecasts, dependencies, and performance to stakeholders.
- Support product discovery by refining roadmap features and evaluating return on investment to guide build decisions.
- Ensure non-functional requirements are defined, tracked, and validated throughout the product lifecycle.
- Engage in agile and scaled agile events, advocating for agile principles and continuous improvement through regular feedback loops.
- Use knowledge of business systems and industry standards to inform product decisions and prioritization.
- Evaluate product metrics and KPIs to suggest data-backed improvements to the Product Manager.
- Lead the product vision and roadmap for fraud detection and prevention capabilities.
- Convert business, risk, and regulatory needs into precise user stories and acceptance conditions.
- Prioritize the product backlog based on fraud risk, customer impact, and return on investment.
- Work with data science teams on fraud models, rules engines, and machine learning initiatives.
- Partner with engineering teams to implement real-time and batch fraud detection solutions.
- Coordinate with Risk, Compliance, AML, and Operations teams to ensure adherence to regulatory standards.
- Define and track key performance indicators such as fraud loss reduction, false positives, approval rates, and customer experience friction.
- Support the full lifecycle of fraud models, including feature updates, monitoring, retraining, and explainability.
- Ensure all solutions meet regulatory and data privacy requirements, including PSD2, GDPR, and PCI DSS.
Work Arrangement
Remote — Bengaluru, India
