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Lead Data Scientist

Posted 2024-09-24

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πŸ’Ž Seniority level: Lead, 5+ years of experience as a Data Scientist or similar role

πŸ“ Location: United States

πŸ” Industry: Music streaming

🏒 Company: Napster

πŸ—£οΈ Languages: English

⏳ Experience: 5+ years of experience as a Data Scientist or similar role

πŸͺ„ Skills: LeadershipData AnalysisMachine LearningAlgorithmsData analysisData scienceCollaboration

Requirements:
  • PhD in Computer Science, Statistics, or a related field (or equivalent experience).
  • 5+ years of experience as a Data Scientist or similar role.
  • Proven experience in leading and mentoring a team of data scientists.
  • Strong expertise in machine learning algorithms (classification, regression, recommendation systems, etc.).
  • Experience with natural language processing techniques.
  • Proficiency in data wrangling, cleaning, and manipulation.
  • Excellent communication and collaboration skills.
  • A passion for music and a strong understanding of the music streaming industry (a plus).
  • Experience working remotely and effectively collaborating with globally distributed teams.
Responsibilities:
  • Build and mentor a team of junior data scientists, fostering a collaborative and learning environment.
  • Define the technical vision and roadmap for the data science team, aligning it with overall product goals.
  • Design and develop advanced search algorithms, including user vector-based models and AI-powered search functionalities.
  • Develop and implement machine learning models to personalize user experience, improve content recommendations, and optimize platform performance.
  • Conduct rigorous data analysis to identify trends, understand user behavior, and extract valuable insights.
  • Collaborate with product managers, engineers, and designers to define data requirements and translate business objectives into actionable data science projects.
  • Communicate complex technical concepts to a non-technical audience in a clear and concise manner.
  • Stay up-to-date with the latest advancements in data science, machine learning, and natural language processing, and explore opportunities to integrate new technologies.
  • Develop and maintain strong data pipelines to ensure data quality and accessibility.
  • Champion best practices in data science methodology and documentation.
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