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DraftKings

Online platform for fantasy sports betting

Senior Data Science Engineering Manager - Marketing

Engineering LeadershipUpdated on Nov 13
Full-timeRemote in USARemote

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field is required.
  • At least 10 years of experience in data science or machine learning engineering, including at least 5 years of formal people leadership or management experience.
  • Proven experience leading data science or machine learning teams through complex initiatives, from setting technical direction through production deployment and ongoing optimization.
  • Advanced proficiency in Python and SQL, along with experience working with modern data platforms and cloud environments.
  • Deep knowledge of machine learning systems, statistical modeling, experimentation frameworks, and the software development lifecycle.
  • Experience applying software engineering, DevOps, and machine learning operations practices, including containerization, automation, testing, deployment, and production monitoring.
  • Strong communication and leadership skills, with the ability to influence cross-functional partners and senior leaders, navigate competing priorities, and clearly communicate technical decisions, risks, tradeoffs, and business impact.

Responsibilities

  • Lead, coach, and develop a high-performing team of data scientists and machine learning engineers, strengthening the technical and leadership capabilities needed to deliver personalization initiatives at scale.
  • Set the team’s strategy, roadmap, and priorities, translating business goals and ambiguous opportunities into high-impact data science and machine learning initiatives with clear measures of success.
  • Partner with senior leaders across Product, Engineering, Marketing, Revenue, and Data Science to identify opportunities, navigate tradeoffs, and connect technical decisions to customer and business outcomes.
  • Guide the development and deployment of machine learning systems across the full model development lifecycle, establishing rigorous standards for design, development, testing, deployment, monitoring, and iteration.
  • Influence the architecture of model-driven experiences, including data pipelines, feature generation, experimentation, batch and real-time serving, observability, and model lifecycle management.
  • Advance software engineering and machine learning operations practices across the team, including automation, containerization, testing, monitoring, and reliable production deployment.
  • Own capacity planning and resource allocation, balancing business value, technical investment, operational needs, and team capacity while adjusting priorities as opportunities and risks evolve.
  • Build a culture of experimentation, technical excellence, and continuous improvement that empowers the team to solve increasingly complex challenges and deliver measurable impact.

Desired Qualifications

  • An advanced degree is preferred.
  • Experience in gaming or a related industry is a plus.

About the Company

DraftKings

Online platform for fantasy sports betting

DraftKings runs an online gaming platform offering daily fantasy sports, sports betting, online casino games, and a marketplace for NFTs. The platform lets users enter cash-prize fantasy contests, place real-money bets on sports, and play casino games, while securely transferring digital assets. It differentiates itself with a broad, diversified product lineup and operates in tightly regulated markets to provide a secure environment. Its goal is to provide a comprehensive, compliant entertainment experience for sports fans, gamblers, and digital collectors while growing revenue across contests, bets, casino games, and NFT trading.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Boston, MA
Founded
2012

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