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VP, Data and AI

Posted 9 days agoViewed

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💎 Seniority level: Vp, 15+ years

📍 Location: United States

💸 Salary: 164880.0 - 300000.0 USD per year

🔍 Industry: Data and AI

🏢 Company: Headspace Sourcing

🗣️ Languages: English

⏳ Experience: 15+ years

🪄 Skills: AWSPythonSQLArtificial IntelligenceMachine LearningTableauData engineeringSparkData analytics

Requirements:
  • 15+ years in data engineering, science, and AI
  • 5+ years in a leadership role
  • Familiarity with AI research tools
  • Experience with machine learning frameworks
  • Knowledge of cloud data platforms (e.g., AWS, Azure)
  • Proficiency in programming languages (Python, R, Java, SQL)
Responsibilities:
  • Oversee design and maintenance of data pipelines
  • Ensure data quality and governance
  • Drive AI and machine learning model development
  • Develop strategic vision for data analytics
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🔥 VP, Data and AI
Posted about 1 month ago

📍 United States

💸 164880.0 - 300000.0 USD per year

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🏢 Company: Headspace👥 11-50WellnessHealth CareChild Care

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. PhD is a plus.
  • 15+ years of experience in data engineering, data science, and AI, with at least 5 years in a leadership role.
  • Proven track record of successfully leading data engineering and AI teams.
  • Familiarity with AI research and development tools and platforms.
  • Strong analytical and problem-solving skills.
  • Extensive experience with machine learning frameworks, generative AI technologies, and big data platforms.
  • Strong understanding of data architecture, governance, and security best practices.
  • Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
  • Knowledge of programming languages such as Python, R, Java, and SQL.
  • Experience in big data technologies (Redshift, S3, Databricks, Datalakes, Spark).
  • Working experience in Looker/Tableau/Amplitude/CoreMetrics.
  • Oversee the design, development, and maintenance of scalable data pipelines and infrastructure.
  • Ensure data quality, integrity, and security across all data systems.
  • Drive the research, development, and deployment of AI and machine learning models.
  • Ensure integration of AI solutions into existing processes.
  • Develop the strategic vision for data analytics and guide analytical methodologies.

AWSPythonSQLArtificial IntelligenceETLMachine LearningTableauData engineeringData modelingData analytics

Posted about 1 month ago
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