Senior Data Product Owner

About the Role

Scientific Games is seeking a working-lead to own product definition quality for the highest-complexity opportunities in the Data Products portfolio. This role focuses on output quality across the full lifecycle, from problem framing through Ready-to-Build handoff, with an initial emphasis on Insight. The ideal candidate will set the standard for the team by demonstrating excellence directly in their work, rather than through directing others.

Responsibilities

• Own output quality across the full product definition lifecycle for the highest-complexity opportunities.
• Set the standard for well-defined opportunities and demonstrate it through individual work.
• Make decisions on what moves forward in the product definition process.
• Develop repeatable methods and templates for Solutions Analysts to use independently.
• Author product definitions, business metric tables, and agent context specs for complex opportunities.
• Lead deployment channel decisions (Databricks-native vs. Teams, Dynamics, or other tools).
• Maintain the business context layer, including metric definitions, metadata, and decision rules for AI products.
• Represent product definition in cross-functional reviews with Platform Engineering and Data Science/ML teams.
• Provide direct feedback, document standards, and offer context to raise the judgment of Solutions Analysts without formal authority.
• Ensure clean handoffs to Platform Engineering and define model requirements and constraints for DS/ML.

Qualifications

• Required:
  • Bachelor’s degree in a relevant field.
  • 7+ years in data, analytics, or product with deep hands-on ownership of end-to-end product definition.
  • Ability to write well-structured product specs, business metric tables, and agent context documents.
  • Technical fluency to make deployment decisions involving Databricks, Teams, and Dynamics without overstepping into engineering scope.
  • Working-lead instinct: effective when close to the work and sets standards through demonstration rather than direction.
  • Influence without authority: shape team approaches through standards, documentation, and coaching without formal reporting relationships.
  • Operating model discipline: maintain clean boundaries with Platform Engineering and DS/ML, even under pressure.
• Desired:
  • Hands-on experience defining AI/agentic products (semantic-layer or metadata-driven products).
  • Familiarity with Databricks, Microsoft Teams, and Dynamics as delivery channels.

Authority

• Set and enforce the Ready-to-Build standard for product definitions.
• Decide what product definition work moves forward to handoff.
• Make deployment channel decisions (Databricks-native vs. Teams, Dynamics, or other).

Requires Approval For

• Roadmap changes and new commitments (owned by the Director).
• Cross-functional escalations that change Platform Engineering or DS/ML scope.
• Prioritizing Discovery Analysts’ work (owned by their manager; this role influences, not directs).

Key Contacts

• Internal: Director, Data Products; Platform Engineering; Data Science/ML; Business stakeholders; Discovery Team.
• External: Technology and platform vendors (e.g., Databricks); Lottery customers.

Physical Requirements

The employee must be able to sit, stand, walk, bend, use hands, operate a computer, and have close and distance vision with the ability to adjust focus. Reasonable accommodations may be made for individuals with disabilities.

Work Conditions

Scientific Games operates in highly regulated gaming and lottery industries. Employees may be required to obtain licenses, undergo background checks, or meet specific standards dictated by law, regulation, or contracts. Consent to a background investigation is a condition of employment.