Head of Data Science and Machine Learning

Head of Data Science and Machine Learning

As the Head of Data Science & Machine Learning, you will be the lead architect of the "Intelligence Layer" for the Sovereign Platform. You will lead an elite team to build, deploy, and scale models that drive top‑line growth, optimize retail and digital operations, and enhance player experiences. This role is focused on high‑velocity commercialization—moving from complex econometric and ML theories to production‑grade products that directly impact the P&L.

• Commercial AI Product Development: Lead design and deployment of specialized models across the Scientific Games portfolio, including:
  • Player Ecosystem:
    Recommender systems for upsell/cross‑sell and Player Lifetime Value (LTV) optimization.
  • Gaming & Revenue:
    Pricing optimization, game design modeling, and advanced forecasting for revenue maximization.
  • Strategic Optimization:
    Portfolio optimization and econometric modeling to guide R&D and capital allocation.
  • Operational Intelligence:
    Supply chain and logistics optimization models to reduce waste and improve retail availability.
• High‑Velocity Deployment Lifecycle: Establish the global standard for the "Three‑Stage Deployment" model:
  • Rapid Prototyping:
    Moving from hypothesis to MVP in weeks.
  • Shadow Deployment:
    Validating model performance against live data without impacting production.
  • Production:
    Seamlessly integrating models into the Sovereign Platform for real‑time inference.
• Monetization & Experimentation: Drive a culture of rigorous A/B testing and experimentation to validate commercial monetization strategy.
• Platform Partnership: Work in lockstep with the Head of Data & AI Platform to ensure ML infrastructure (MLflow, Databricks) supports high‑scale, low‑latency model serving.
• Leadership: Recruit and mentor top‑class talent to maintain high technical standards and commercial focus.

• 10+ years in Data Science/ML leadership in a high‑transaction industry (Gaming, Fin Tech, or E‑commerce) where model accuracy directly dictates margin.
• Methodological Mastery:
  Deep expertise in econometrics & forecasting, optimization, and behavioral modeling.
• Full‑Stack ML Awareness:
  Strong understanding of deployment plumbing—Docker, Kubernetes, API integration for real‑time model serving.
• Platform Expertise:
  Hands‑on experience with Databricks, Spark, and MLflow.
• Advanced degree (Ph.D. or Masters) in a quantitative field (Economics, Math, Statistics, CS, or Operations Research).
• Years of related experience: 15–18 years.

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, 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 while working with computer and business equipment.

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 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.