Senior Data Science Engineering Manager

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

📋 Description

• Lead, mentor, and cultivate a high-performing team of data scientists and machine learning engineers.

• Define the team’s strategic direction, roadmap, and priorities, converting business objectives and ambiguous prospects into impactful data science and machine learning projects.

• Collaborate with senior leaders from Product, Engineering, Marketing, Revenue, and Data Science to uncover opportunities, manage trade-offs, and link technical decisions to customer and business results.

• Oversee the development and deployment of machine learning systems throughout the complete model development lifecycle.

• Set standards for design, development, testing, deployment, monitoring, and iteration.

• Shape the architecture of model-driven experiences, encompassing data pipelines, feature generation, experimentation, batch and real-time serving, observability, and model lifecycle management.

• Enhance software engineering and machine learning operations practices, focusing on automation, containerization, testing, monitoring, and dependable production deployment.

• Manage capacity planning and resource distribution.

• Foster a culture of experimentation, technical excellence, and continuous enhancement.

• Establish the strategy for data science and machine learning to deliver personalized experiences to millions of customers.

⛳️ Requirements

• Bachelor’s Degree in Computer Science, Data Science, Machine Learning, or a related discipline.

• Minimum of 10 years of experience in data science or machine learning engineering.

• At least 5 years of formal experience in people leadership or management roles.

• Demonstrated experience in leading data science or machine learning teams through intricate projects, from establishing technical direction to production deployment and continuous optimization.

• Advanced proficiency in Python and SQL.

• Experience with modern data platforms and cloud environments.

• Extensive knowledge of machine learning systems, statistical modeling, experimentation frameworks, and the software development lifecycle.

• Familiarity with software engineering, DevOps, and machine learning operations practices, including containerization, automation, testing, deployment, and production monitoring.

• Excellent communication and leadership abilities, capable of influencing cross-functional partners and senior leaders, managing competing priorities, and effectively conveying technical decisions, risks, trade-offs, and business impacts.

• Experience in gaming or a related field is advantageous.

• May need to obtain a gaming license issued by the relevant state agency as a condition of employment.

🏝️ Benefits

• Bonus

• Equity

• Benefits as applicable