Scientific Games Corporation

Senior Data Product Owner

Scientific Games Corporation$110K — $130K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in a relevant field
  • 7+ years in data, analytics, or product with deep end-to-end ownership of product definition
  • Ability to write structured product specs, business metric tables, and agent context documents
  • Technical fluency to make deployment decisions involving Databricks, Teams, and Dynamics
  • Instinct to lead close to the work and set standards by example
  • Influence peers and Solutions Analysts without formal authority through standards and direct coaching
  • Discipline in managing boundaries with Platform Engineering and DS/ML

Responsibilities

  • Own output quality throughout the product definition lifecycle
  • Establish and demonstrate standards for well-defined opportunities
  • Decide which product definitions progress to handoff
  • Develop repeatable methods and templates for Solutions Analysts
  • Author key documentation for complex product opportunities
  • Lead deployment decisions for various end-user tools
  • Maintain business context metrics and decision rules for AI products

Benefits

  • Opportunity to shape standards and practices in product definition
  • Work in a dynamic, cross-functional environment
  • Chance to directly influence team performance and outputs
  • Engage with advanced data products and technology platforms
  • Potential for impactful contributions to high-complexity projects
Full Job Description
Position Summary

Job Summary:

Working-lead role that owns product definition quality for the highest-complexity opportunities in the Data Products portfolio - output quality across the full lifecycle, from problem framing through Ready-to-Build handoff. Insight is the starting focus. This role sets the standard for the rest of the team by demonstrating it directly, not by directing others' work.

Scope:

Owns product definition quality for the highest-complexity opportunities in the Data Products function, working as an individual contributor. Partners with Platform Engineering, Data Science/ML, and business stakeholders. Sets the standard Solutions Analysts follow - without formal authority over their day-to-day work or performance. Reports to the Director, Data Products.

Essential Job Functions:
  • Own output quality across the full product definition lifecycle, from problem framing through Ready-to-Build handoff, on the highest-complexity opportunities
  • Set the standard for what a well-defined opportunity looks like - and demonstrate it directly in your own work
  • Make the call on what moves forward
  • Build repeatable methods and templates that Solutions Analysts can execute without your involvement in every decision
  • Author product definitions, business metric tables, and agent context specs for the highest-complexity opportunities
  • Lead deployment channel decisions - Databricks-native vs. Teams, Dynamics, or another end-user tool
  • Maintain the business context layer: metric definitions, metadata, and decision rules that keep AI products reasoning correctly
  • Represent product definition in cross-functional reviews with Platform Engineering and DS/ML
  • Raise the judgment of Solutions Analysts through direct feedback, documented standards, and context - without a reporting relationship
  • Ensure handoffs to Platform Engineering are clean, and define for DS/ML what models must produce and within what constraints


Qualifications

Required:
  • Bachelor's degree in a relevant field
  • 7+ years in data, analytics, or product, with deep hands-on ownership of product definition work end-to-end (people-management experience not required)
  • Product definition depth - can write a well-structured product spec, business metric table, and agent context document, and knows the difference between a complete one and one that causes problems downstream
  • Technical fluency without engineering scope - understands what Databricks, Teams, and Dynamics can do well enough to make deployment decisions, without reaching into Platform Engineering's territory
  • Working-lead instinct - most effective close to the work, and sets standards by demonstrating them rather than directing others
  • Influence without authority - can shape how Solutions Analysts and peers approach their work through standards, documentation, and direct coaching, with no reporting relationship
  • Operating model discipline - manages the boundary with Platform Engineering and DS/ML cleanly, and holds that line 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 To:
  • 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 physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to sit, stand, walk, bend, use hands, operate a computer, and have specific vision abilities to include close and distance vision, and ability to adjust focus working with computer and business equipment.

Work Conditions

Scientific Games, LLC and its affiliates (collectively, "SG") are engaged in highly regulated gaming and lottery businesses. As a result, certain SG employees may, among other things, be required to obtain a gaming or other license(s), undergo background investigations or security checks, or meet certain standards dictated by law, regulation or contracts. In order to ensure SG complies with its regulatory and contractual commitments, as a condition to hiring and continuing to employ its employees, SG requires all of its employees to meet those requirements that are necessary to fulfill their individual roles. As a prerequisite to employment with SG (to the extent permitted by law), you shall be asked to consent to SG conducting a due diligence/background investigation on you.

This job description should not be interpreted as all-inclusive; it is intended to identify major responsibilities and requirements of the job. The employee in this position may be requested to perform other job-related tasks and responsibilities than those stated above.

About Scientific Games Corporation

Light & Wonder, Inc., formerly Scientific Games Corporation, is an American corporation that provides gambling products and services. The company is headquartered in Las Vegas, Nevada, with lottery headquarters and production plant in Alpharetta, Georgia. Light & Wonder's gaming division provides products such as slot machines, table games, shuffling machines, and casino management systems. Its brands include Bally, WMS, and Shuffle Master.
Learn more about Scientific Games Corporation
Size
9,500 employees
Market Cap
$5.6 billion
Industry
Net Income
-$569 million
Founded
1973
5 Year Trend
-5.7%
Revenue
$2.7 billion
NASDAQ

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