Vice President, Data Science and Analytics 1355 views

As the VP of Data Science & Analytics, you will be responsible for collecting, managing, and analyzing user data and product data to provide business intelligence solutions for Product, Marketing, Finance, and Business teams. Manage a team of action-oriented data scientists and analysts, lead and promote our data-focused culture, and act as a key stakeholder in enhancing their data technologies. This position reports directly to their Chief Experience Officer and is expected to have a high impact on the organization.

What You Have

• • Bachelor’s degree in Computer Science, Economics, Information Systems, Statistics, Operations Research, Applied Math, or another related field, Master’s Degree Preferred
  • 10+ years of experience in data science, data analytics, web analytics, and marketing analytics
  • 5+ years of experience with data warehouses and ETL
  • 7+ years of experience managing data analysts, business analysts, data scientists, data engineers, and ETL engineers
  • Expert experience with SQL for data transformations, profiling, and query tasks
  • Experience with statistical and machine learning tools: Python, R, SAS, etc.

What You’ll Do

• Identify, collect, prepare, and analyze customer and product data across a wide range of domains
• Set the vision and strategy for analytics with a focus on creating customer value
• Integrate data collection, data quality, and core model output into production; apply data mining techniques to uncover actionable business insights
• Ensure and improve data integrity, data accuracy, and data quality
• Work with the data engineering team to build a scalable data infrastructure that enables activity tracking, audience profiling, and other data analytics
• Establish best practices for big-data technologies, tools, and own processes related to model section, accuracy, and efficiency
• Identify new data sources to enhance analytics
• Collaborate with all teams to find growth levers and optimization opportunities
• Offer actionable business recommendations based on empirical data and external factors
• Develop and manage audience profiling
• Manage and improve the LTV model
• Manage user journey path, on-page activity, and other customer behavior
• Establish a long-term roadmap for providing deep business intelligence