Senior Data Scientist, Cloud Gaming – Prescriptive Analytics and Optimization

This is a fully remote position, open to applicants in California.

📋 Description

• Develop and implement scalable machine learning, artificial intelligence, and optimization models to improve demand forecasting, optimize capacity allocation, and create user-specific feature engineering for real-time cloud gaming services.

• Create reusable frameworks for data ingestion, processing, and analysis to facilitate dynamic user interventions aimed at achieving targeted business results.

• Gain and apply in-depth knowledge of the product and software stack to identify and resolve data inconsistencies, thereby enhancing model performance, particularly in terms of optimization outcomes.

• Recognize, analyze, and interpret trends or patterns within complex datasets using both supervised and unsupervised learning techniques, leading to informed prescriptive solutions.

• Design and implement enhancements to real-time prescriptive scheduling pipelines utilizing methods such as linear programming and constraint optimization to improve capacity utilization and user retention.

• Elevate organizational productivity by mining vast amounts of data for actionable insights that benefit both business and engineering, frequently through prescriptive recommendations.

• Collaborate with diverse partners to understand requirements, design robust solutions, and steer the team towards delivering impactful outcomes.

• Utilize agentic AI to provide top-tier automation and programming solutions for intricate analytical challenges.

⛳️ Requirements

• A BS/MS (or equivalent experience) with over 6 years of experience, or a PhD in Data Science, Computer Science, Operations Research, Statistics, Applied Mathematics, or related quantitative disciplines, with a strong focus on prescriptive analytics and optimization.

• Solid knowledge and hands-on experience in probability, statistics, AI/ML, prescriptive modeling, and optimization techniques (e.g., linear programming, network flow, decision theory, and multi-armed bandit).

• Proficient coding skills, including the ability to write clean, testable, maintainable, and extensible code primarily in Python, along with familiarity with libraries or tools pertinent to optimization (e.g., Google OR-Tools).

• Experience with commonly used tools for data storage and processing, including tackling challenges associated with running large-scale software across extensive clusters.

• Extensive experience in data cleaning, aggregation, transformation, and extraction, with an understanding of how data quality affects performance.

🏝️ Benefits

• Equity

• Benefits