Journo Jobs

WSJ seeks a senior data journalist

The Wall Street Journal’s Data Team is seeking a creative data journalist with a strong background in causal inference, economics, political science or quantitative social sciences, with a particular emphasis on explaining real-world phenomena. The ideal candidate should have a deep understanding of how to leverage data to uncover causal relationships, a natural and wide-ranging curiosity about how the world works and the ability to identify clever and revealing natural experiments.

You will:

  • Develop and implement statistical and causal inference models to analyze and interpret complex datasets, focusing on uncovering relationships and patterns that explain real-world events.
  • Collaborate with journalists to uncover data-driven stories.
  • Conduct rigorous methodology assessments to determine the validity and reliability of data, and evangelize statistical rigor across the newsroom.
  • Balance theoretical knowledge with practical application, and communicate findings clearly and effectively to non-technical audiences.

You have:

  • Previous experience in journalism or working with media organizations is a plus, but not required.
  • 5+ years of post-graduate experience in data science.
  • An MS with research experience or PhD in data science, statistics, economics, quantitative social sciences, or a related field—or equivalent, documented experience.
  • A strong theoretical foundation in areas such as statistical modeling or causal inference, coupled with a practical approach to data analysis.
  • Proficiency in statistical software and programming languages (e.g., R, Python, SQL) and their use in large datasets with advanced statistical techniques, such as regression analysis, machine learning and causal modeling. Familiarity with modern data visualization tools would be helpful.
  • Excellent problem-solving skills and ability to think critically and creatively with a demonstrated ability to translate complex data findings into engaging and understandable narratives.

To apply:

Please include a brief example (no more than 200 words) demonstrating how you would use data to produce a journalistic story.

This could be a short outline of an actual investigation you’ve conducted or a hypothetical scenario using publicly available data.

Explain what data you’d analyze, how you’d identify a newsworthy angle and how you’d present the findings to a general audience.

Focus on storytelling and clarity, not just technical methods

Deadline is December 20.

To apply, go here.

Chris Roush

Chris Roush was the dean of the School of Communications at Quinnipiac University in Hamden, Connecticut. He was previously Walter E. Hussman Sr. Distinguished Professor in business journalism at UNC-Chapel Hill. He is a former business journalist for Bloomberg News, Businessweek, The Atlanta Journal-Constitution, The Tampa Tribune and the Sarasota Herald-Tribune. He is the author of the leading business reporting textbook "Show me the Money: Writing Business and Economics Stories for Mass Communication" and "Thinking Things Over," a biography of former Wall Street Journal editor Vermont Royster.

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