Senior Data Scientist, Vox Media

• Familiarity with Python and SQL, particularly in the context of data science and analytics
• Self-sufficiency. You feel comfortable owning a problem end-to-end, identifying the right approach, writing transformation logic to create a dataset, building a model, and a tool to consume its output
• Experience working with a cloud-based data warehouse, like BigQuery or Snowflake. We use BigQuery with dbt for transformation and Dagster for orchestration
• Demonstrable experience using data science to solve a business problem. This does not need to be cutting-edge ML. We’re looking for someone who can evaluate tradeoffs and choose the right solution for the problem, even if that’s rule-based logic
• Adept at leveraging AI both to accelerate your own work and to automate data science and analytics workflows. Expect to use AI regularly in this role to understand new problem spaces and common approaches, write code and documentation, and build tools
• Some experience with experiment design and measurement

Desirable

• As a Data Scientist focused on our Consumer Revenue businesses, you’ll work on problems that fuel the next stage of growth
• You will build tools, models, and frameworks that push our understanding of what our paying subscribers care about, what marketing strategies work and the impact they have, and what to try next
• This role is on Vox Media’s Data team, which is responsible for maintaining our data warehouse and for a number of backend systems that power personalized audience experiences across our brands, like search and personalized feeds in the Eater app and reading recommendations on New York magazine
• Solve problems like churn risk modeling, LTV calculations, retention impact measurement, paid marketing attribution, etc. and build tools and integrations to make their outputs actionable
• Define measurement frameworks and build tools and dashboards to measure impact of initiatives across acquisition, engagement, and retention
• Work closely with team leads on the Data and Consumer Revenue teams to understand problems, discuss approaches, and make decisions about approaches and tradeoffs
• In partnership with data engineers and analysts, help with ongoing measurement and reporting needs for this business
• Occasionally work in partnership with others on audience-facing initiatives like recommendations