Principal Data and Machine Learning Scientist

Scientific Games • Alpharetta, GA

6h

About The Position

Scientific Games: Scientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries. From cutting-edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we elevate play every day. We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation, legendary performance, and unwavering security to responsibly propel the global lottery industry ever forward. Position Summary As the Principal Data & ML Scientist, you are the technical vanguard of Scientific Games. Your mission is to bridge the gap between high-level business problems and world class algorithmic solutions. You will be responsible for designing and deploying the most complex models in our portfolio - from pricing engines that dictate margin to recommender systems that drive player engagement. This is a role for a "full-stack" scientist: someone who possesses deep theoretical mastery but is equally obsessed with building production-quality code.

Requirements

• Education: Minimum of a Master’s degree (Ph.D. preferred) in a highly quantitative field such as Economics, Statistics, Mathematics, Operations Research, or Computer Science.
• Technical Mastery: 10+ years of experience in Data Science with a track record of building models that directly dictate business margin.
• Forecasting & Econ: Expertise in causal inference and time-series analysis.
• Optimization: Deep knowledge of linear/non-linear programming and resource allocation.
• Recommenders: Proven experience building large-scale personalization or recommendation engines.
• Domain Expertise: Robust background in B2B or Retail environments. You must understand the "physics" of supply chains, pricing elasticities, and customer lifecycle management.
• Software Engineering Rigor: Proficiency in Python, Spark, and SQL. You must be comfortable working in a Databricks/Lakehouse environment and have a solid understanding of Docker, APIs, and production deployment patterns.
• Strategic Diplomacy: The ability to influence technical roadmaps and "sell" a mathematical approach to business leaders who prioritize outcomes over algorithms.

Responsibilities

• Algorithmic Architecture & Excellence Lead "Intelligence" Design: Design the core algorithms for the Sovereign Platform’s most critical functions, including multi-horizon Forecasting, Portfolio Optimization, and Revenue Management.
• Commercial Modeling: Architect and build high-impact models for Forecasting, Portfolio and Pricing Optimization, Upsell/Cross-sell, and Player LTV.
• Technical Bar-Setter: Establish the "Definition of Done" for model quality, including rigorous validation, back-testing, and drift-monitoring standards.
• Production-Grade Science Research to Reality: Partner with the Platform Engineering team to ensure models are designed for high-velocity deployment. You don't just hand over a notebook; you ensure the science is robust enough for real-time inference and scalable shadow deployments.
• MLOps Advocacy: Champion the use of Feature Stores, MLflow, and automated retraining pipelines to ensure the long-term health of our production assets.
• Strategic Business Translation B2B & Retail Mastery: Apply deep domain expertise to translate complex retail and gaming business processes into mathematical objective functions.
• The "So What": Distill complex model outputs into actionable business insights for non-technical stakeholders, ensuring our "Intelligence Layer" directly impacts the P&L.
• Mentorship & Global Leadership Talent Magnet: Act as a mentor to Senior and Staff scientists across our hubs.
• Peer Review: Lead technical reviews for high-stakes projects, ensuring that any model deployed under the "Sovereign" banner is mathematically sound and ethically governed.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior