Data Analyst, Subscriber Experience
@ The New York Times

New York, NY
$91,000
On Site
Full Time
Posted 4 days ago

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XXXXXXXXXX XXXXXXXXXXXXX XXXXXX******* @nytimes.com
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Job Details

About The Role

The New York Times is searching for a Data Analyst, Subscriber Experience to join their Data and Insights Group (DIG). You will work closely with Product, Engineering, Design, and PMO teams to deliver data insights that inform product and feature development focused on engaging millions of users with high-quality journalism.

Responsibilities

  • Write SQL queries to pipeline and analyze big data.
  • Create data-oriented analyses for high-level partners.
  • Develop best practices for experimental design.
  • Structure data and use visualization tools.
  • Participate in all phases of analytic work from problem definition to results representation.
  • Collaborate with partners to identify performance trends and data-driven solutions.
  • Uphold journalistic independence and a commitment to truth.

Basic Qualifications

  • 1+ years experience working with data teams or a related quantitative degree.
  • Proficiency in SQL and relational databases.
  • Experience with data visualization tools like Mode, Tableau, or Looker.

Preferred Qualifications

  • Experience in Python or R.
  • Experience with dbt and big data environments such as Google BigQuery or AWS.
  • Familiarity with version control using Github.
  • Experience with A/B testing and applying statistics to strategic problems.

Compensation & Work Environment

The annual base pay ranges between $88,000 - $95,000 USD. This position is hybrid and is based in New York, NY.

Key skills/competency

  • SQL
  • Data Analysis
  • Data Visualization
  • Experiment Design
  • Big Data
  • Python
  • R
  • dbt
  • Analytics
  • Journalism
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How to Get Hired at The New York Times

🎯 Tips for Getting Hired

  • Research The New York Times culture: Study their mission, news, and diversity values.
  • Customize your resume: Highlight data analysis and SQL skills.
  • Prepare sample projects: Show data visualization work examples.
  • Practice technical interviews: Review SQL, Python, and analytics challenges.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query optimization techniques.
Practice data visualization tool exercises.
Brush up on Python/R scripting basics.
Explore big data environment tutorials.

Behavioral Questions

Describe teamwork in cross-functional projects.
Explain handling tight deadlines under pressure.
Discuss a challenging data analysis project.
Share experiences with feedback and collaboration.

Frequently Asked Questions