VP, DIG - Growth Analytics

You need to sign in or
create an account to save a job.
Job Description

At the New York Times, we are working towards an ambitious subscriber goal for 2025. The New York Times is seeking a VP to lead the Subscription Growth team within the Data and Insights Group.

Subscription Growth is responsible for partnering with product & engineering to maximize total subscriber numbers profitably. This team consists of groups focused on retention, conversion, and the underlying platforms and data that support these metrics. Team members design and analyze experiments, explore areas of strategic opportunity, design measurement plans against KPIs, and develop reporting & dashboards for monitoring product health & delivering insight. This position will be responsible for the direction of the analytics team, including partnering with product leadership to set long-term roadmaps and strategy, ensuring the quality and impact of team output, and developing the people leaders and ICs within the team. The role requires strong strategic and tactical viewpoints, leadership skills, a strong foundation in analytics, and endless curiosity.

  • Partners with functional leads (product, design, engineering) across the Growth mission to set strategy, roadmap and OKRs
  • Fosters an inclusive, welcoming, cohesive culture within the Data and Insights function as a whole and their team in particular
  • Leads, hires, onboards, and develops talent within their team, including managing people leaders
  • Is responsible for the quality and direction of analytics team's work
  • Collaborates closely with counterparts in Data & Insights and Finance on projects that span multiple missions
  • Represent the best practices of the Data & Insights group to both internal and external partners

Desired Qualifications:
  • 10+ years of progressively complex experience in analytics; experience with subscriber analytics preferred
  • Experience working with product teams
  • Quantitative degree
  • Mastery of SQL
  • Insight using online measurements and analytics, with the ability to provide meaningful and actionable insights and analysis.
  • Mathematical or statistical background. Demonstrated knowledge of multivariate statistical and modeling techniques.
  • Experience in data visualization/reporting and data viz tools such as Mode, Looker, or Tableau.
  • Strong communication and interpersonal skills, and ability to work seamlessly with multiple stakeholders in a cross functional team of analysts, technologists, operations and product managers.
  • People leadership experience - preferably experience as a leader of leaders
  • Extensive experience in experiment design, analysis and modeling
  • Experience with big data environments such as Google BigQuery


The New York Times is committed to a diverse and inclusive workforce, one that reflects the varied global community we serve. Our journalism and the products we build in the service of that journalism greatly benefit from a range of perspectives, which can only come from diversity of all types, across our ranks, at all levels of the organization. Achieving true diversity and inclusion is the right thing to do. It is also the smart thing for our business. So we strongly encourage women, veterans, people with disabilities, people of color and gender nonconforming candidates to apply.

The New York Times Company is an Equal Opportunity Employer and does 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 New York Times Company will consider qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local "Fair Chance" laws.