Principal Data Analyst, Acquisition

The Washington Post

The Washington Post's Data and Analytics department is integral in shaping strategic and operational decisions. This role, as a Principal Data Analyst, is crucial in driving subscriber growth through data-led strategies. The analyst will work with various departments to derive meaningful insights and solutions from vast datasets.

In this role you can expect to have the responsibilities:

• Define and implement data-driven strategies to enhance customer acquisition.
• Analyze subscription performance and campaign ROI.
• Create predictive models for acquisition trends and lifetime value.
• Develop and present analyses to stakeholders, including executives.
• Design dashboards for tracking key performance indicators.
• Extract insights from large datasets using advanced analytics.
• Collaborate with marketing and product teams on campaign experiments.
• Mentor junior analysts and provide statistical expertise.
• Work with SQL, Python, R, Tableau, and other BI platforms.

This role comes with the following benefits:

• Competitive medical, dental, and vision coverage.
• Company-paid pension and 401(k) match.
• Vacation and paid sick leave.
• Paid parental leave.
• Mental health resources.
• Backup care services.
• Pet insurance.
• Digital subscription to The Post.
• Leadership and career development programs.

This role requires you to have:

• Data analysis expertise with a focus on subscription businesses.
• Proficiency in SQL, Python, and data visualization tools.
• Strong communication and data storytelling skills.
• Experience in relational databases and advanced SQL.
• Ability to multitask and manage project priorities.

You would benefit from having:

• Experience with customer segmentation and predictive modeling.
• Familiarity with enterprise Web Analytics systems.
• Knowledge of A/B testing and experimental design.

The Washington Post values diversity and innovation, fostering a multicultural and inclusive workplace. Benefits are comprehensive, with variations based on employment status and location.