Data Analyst, Subscriber Experience at The New York Times

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

95000.0

Posted On

04 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Analysis, Data Visualization, Python, R, Experiment Design, A/B Testing, Statistical Analysis, Data Structuring, Visualization Tools, Relational Databases, Big Data, Github, Google BigQuery, AWS, dbt

Industry

Newspaper Publishing

Description

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 As part of the Data and Insights Group (DIG), you will join a large community of accomplished analysts who partner with Product, Engineering, Design, and PMO teams across the business. You will support the Subscriber Experience Mission, focused on delivering insights alongside product and feature development that bring the News to our readers. You will work directly with company partners to help us understand and work on opportunities to engage millions of users with NYT journalism through product plans across different platforms. You will report to our Director, Data and Insights, Subscriber Experiences. This is a hybrid position based in New York, NY. Responsibilities: You will write SQL to pipeline and analyze big data You will apply analytical reasoning to create data-oriented analyses to be presented to high-level partners in slide decks and memos to guide team strategy You will develop best practices for experiment design, including advising on hypothesis generation, sample size, and counter metrics You will democratize data and insights through skillful data structuring and use of visualization tools You will participate in and sometimes lead all phases of analytic work: from problem definition to representation of results You will work with company partners to understand our performance and develop data-driven solutions 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: 1+ years of experience working with data teams to deliver analysis or a quantitative degree or certification. Proficiency in SQL and experience working with relational databases 1+ years of experience with data visualization tools such as Mode, Tableau, or Looker Preferred Qualifications: 1+ years of experience in Python or R 1+ years of experience with dbt Familiarity with Google BigQuery, AWS, or other big data environments Comfort with version control (Github) 1+ years of experience A/B testing or applying statistics to strategic problems REQ-019072 The annual base pay range for this role is between: $88,000—$95,000 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 encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For information about The New York Times' privacy practices for job applicants click here. Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times. If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.

Responsibilities

You will write SQL to pipeline and analyze big data while applying analytical reasoning to create data-oriented analyses. You will work with company partners to understand performance and develop data-driven solutions.