Original listing text, shown exactly as published by the company.
What you’ll do
- Use data to shape Pinterest’s product adoption strategy. From understanding the audience to identifying/sizing the opportunity and executing in-product experiments, you will translate data into insights and action, communicate recommendations and learnings to the broader organization and feed insights to update the creative best practices.
- Develop product and marketing measurement plans, learning agenda and goals to ensure team is maximizing learning at every opportunity and delivering actionable insights to inform future iterations.
- Lead end-to-end experimentation effort from designing, setting up to comprehensive reporting on campaign/test performance across a host of metrics such as business, behavioral, product adoption and channel performance metrics.
- Build and maintain central reporting dashboards to improve visibility and accessibility of product lifecycle, GTM performance and in-product marketing impact across team and stakeholders.
- Socialize actionable, timely insights and findings with cross functional partner to inform/influence key decision and planning.
- Establish best practices and center of excellence on product marketing measurement and approaches.
What we’re looking for
- Exceptional data analysis skills. 8+ years of experience analyzing data in a fast-paced, data-driven environment (e.g. consumer tech). Expert in SQL or Python/R with experience in leveraging a variety of analytical tools and dashboards to visual data such as Tableau or Apache Superset. Experienced in designing and setting up global product and marketing measurement frameworks, executing A/B tests and comprehensive analysis, from data-driven user segmentation (behavioral, demographic, etc.), designing product growth experiments (A/B and multivariate tests), to funnel analysis, with a proven track record of success.
- Entrepreneurial self-starter. You thrive in a fast-moving, ambiguous environment, and are independently capable of seeking information, corralling resources, and delivering results without waiting for direction. Scrappy, creative problem solver who is able to work around constraints to maximize test and learn opportunities. Attention to detail and commitment to high-quality results-oriented output. Comfortable with technical work, can use self-serve tooling without dedicated Engineering support.
- Strong communication skills. You can move seamlessly between conversing with engineers or PMMs and leading presentations with senior executives.
- High-energy, positive team player. You have a proven ability to build strong working relationships with business partners; this is a highly cross-functional role, so a low ego and a high instinct for collaboration are musts. Demonstrated ability to work with cross-functional stakeholders to identify and prioritize data needs and influencing decision making through data.
- Keen aptitude to scale the team. Help build out processes for a small (but mighty) team. Help build our influence across the organization to tackle each of the above for your coverage area.
- Graduate degree in a quantitative field such as mathematics, statistics, computer science or engineering (or equivalent work experience).
Relocation Statement
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
- This role will need to be in the office for in-person collaboration 1-2 times every 6 months, and therefore can be situated anywhere in the country.
#LI-REMOTE
#LI-PW1
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
