Role: AI Data Product Lead
Duration: 6+ Months
Location: Remote/ Houston, TX
Primary Skills : AI, Azure
Job Description: AI Data Product Lead
- Role Overview:
- Lead the development of a commercial data product leveraging payment, settlement, and dispute data, with a focus on predictive, prescriptive, and AI-driven analytics for merchants and independent software vendors.
- Key Responsibilities:
- Evaluate and understand the current Architecture and data to create scalable, modern analytics products.
- Collaborate with managed service providers and AI vendors (e.g., Wisdom AI, Copilot) to guide technical direction and ensure business alignment.
- Design and implement use cases for aggregated issuer data, benchmarking, and actionable insights for merchants (e.g., customer demographics, repeat business, competitor analysis, event-driven predictions).
- Build and prototype small, market-ready use cases, iterating based on feedback and evolving industry standards.
- Ensure data quality, governance, and security in all solutions, working within Azure environments (Cosmos, Synapse, Power BI, and potentially Microsoft Fabric).
- Provide help in developing generative and agentic models for business users to interact with data and receive automated insights and alerts.
- help bridge gaps between business vision and technical execution.
- Required Skills:
- Proven experience in data architecture, analytics, and AI/ML product development.
- Strong understanding of payment data, merchant analytics, and data privacy (PII, aggregation).
- Hands-on expertise with Azure data stack (Cosmos, Synapse, Power BI, Fabric).
- Ability to work in a startup environment with limited resources and high ambiguity.
- Leadership, vision, and the ability to translate business needs into technical solutions.
- Experience collaborating with external vendors and managed service providers.
- Preferred:
- Experience with restaurant or retail analytics.
- Familiarity with benchmarking, predictive modeling, and agentic AI solutions.
- Ability to design and implement data-driven products for commercial resale