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Director, Data Science

Posted 6 months agoInactiveViewed

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πŸ’Ž Seniority level: Director, 5+ years of relevant data science and analytics experience

πŸ“ Location: United States

πŸ” Industry: AI-powered analytics

🏒 Company: RockstarπŸ‘₯ 11-50LifestyleRetailFashionLeisureApparel

πŸ—£οΈ Languages: English

⏳ Experience: 5+ years of relevant data science and analytics experience

πŸͺ„ Skills: AWSLeadershipPythonMachine LearningPeople ManagementStrategyAlgorithmsData scienceCommunication SkillsCollaboration

Requirements:
  • 5+ years of relevant data science and analytics experience.
  • 3+ years of experience hiring and managing data scientists, analysts, and/or engineers.
  • Strong leadership skills with the ability to identify the best ideas, socialize them, and rally the team around them.
  • Demonstrated experience creating production ML pipelines (training, scoring, leveraging in real-time systems).
  • Expert knowledge of modern machine learning algorithms (regression, classification, random forests, clustering, optimization, etc.) and statistical inference.
  • Deep understanding of Data Warehousing principles and practices.
  • Hands-on experience and expertise with Python Frameworks.
  • Experience with the AWS data ecosystem and technologies.
  • Excellent verbal and written communication skills.
  • Strong people management, mentoring, and interpersonal skills.
  • Ability to thrive in a fast-paced, entrepreneurial, high-energy environment.
Responsibilities:
  • Lead, manage, and inspire a team of data science engineers.
  • Help drive a data-first culture where data is leveraged in decision-making.
  • Hire, mentor, and grow a world-class data team.
  • Understand business and technical requirements to set priorities.
  • Communicate Data Team goals, priorities, timelines, and obstacles to execs and other stakeholders.
  • Directly contribute to team goals with 50-75% hands-on involvement.
  • Develop and codify processes and best practices for modeling, testing, and analytics.
  • Collaborate with the team and CTO to define and direct the technical strategy for the data science ecosystem.
  • Effectively balance short-term delivery with long-term direction and value.
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