Senior Analyst, Growth Analytics, Retention

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. 

About the Role

The Times is looking for a creative senior data analyst who is passionate about data and eager for the opportunity to support our journalistic mission. As part of the Data and Insights Group (DIG), you will join a large community of data analysts who partner with Product, Engineering, Design, and PMO teams across the business. You will support the Algorithmic Targeting (ALTA) team's retention and revenue pod, which develops, deploys, tests, and analyzes machine learning models. You will report to the Executive Director of Growth Analytics.

 

Responsibilities:

• You will write SQL to pipeline and analyze big data

• You will develop dashboards to expand access to data and analytics

• You will perform data-oriented analyses and present your insights to high-level partners in slide decks and memos to guide team strategy

• You will run A/B Tests and provide scope and analysis

• You will investigate and visualize relationships between our models' outputs and user segments and behavior, to motivate algorithm improvements

• You will demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

 

Basic Qualifications:

• 3+ years of experience working with data analytics or data science teams to deliver reporting and analysis

• Proficiency in SQL and experience working with relational databases

• 3+ years of experience communicating cross-functionally, presenting key insights to team members and company partners

• Experience in Python or R

• 1+ years of experience with data visualization tools such as Mode, Tableau, or Lookr

 

Preferred Qualifications:

• Familiarity with Google BigQuery, AWS, DBT, or other big data environments

• Familiarity with machine learning techniques

• 1+ years of experience applying statistics to strategic problems

• 1+ years of experience with A/B testing

 

#LI-Hybrid

REQ-018334

The annual base pay range for this role is between:$101,000—$110,000 USD

 

The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all  backgrounds to apply.

We are  an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics.  The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here. 

The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response.

The Company will further consider qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable "Fair Chance" laws. 

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