- Company Name
- Incard
- Job Title
- Senior Product Owner (Data / AI)
- Job Description
-
Job Title: Senior Product Owner (Data / AI)
Role Summary: Lead end‑to‑end ownership of data‑driven product domains (analytics, forecasting, anomaly detection, AI‑powered financial insights) within a fintech platform. Act as a mini‑CEO for the intelligence layer, translating data science outcomes into actionable product features for business users.
Expectations: • Own vision, scope, quality, and outcomes with minimal supervision.
• Translate complex data capabilities into clear, high‑value product experiences.
• Make rapid decisions on model‑build vs inference vs automation while ensuring explainability and usability.
• Operate autonomously in ambiguous, probabilistic environments.
Key Responsibilities: • Define product strategy, use cases, and success metrics for analytics & AI services.
• Partner with data scientists to shape models, assumptions, and outputs.
• Write structured product requirements, specs, acceptance criteria, and break initiatives into milestones.
• Collaborate with front‑end, mobile, back‑end, and customer teams to align data products with business and regulatory needs.
• Validate data quality, Assumptions, and edge cases; manage risk, compliance, and AI governance.
• Iterate on launched features based on user feedback, usage data, and performance metrics.
• Mentor and help build the future data/AI squad (hiring, onboarding, squad culture).
Required Skills: • 4–7+ years in data‑product, analytics‑product, or data‑science‑led product roles.
• Strong background in data science, analytics, or applied machine learning.
• Experience turning models into production‑ready product features.
• Deep understanding of metrics, experimentation, forecasting, and data pipelines.
• Ability to write clear, structured specs for AI‑driven systems.
• Excellent communication, stakeholder management, and storytelling with complex concepts.
• Comfortable with ambiguity, noisy data, and rapid iteration.
Required Education & Certifications: • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field. • No specific certifications required (though expertise in ML platforms or BI tools is a plus).