What You'll Do: - Develop a comprehensive understanding of the Pinterest ecosystem, collaborating with Core and Monetization leadership to navigate complexities and influence effectively across various pods and organizations. Example projects include: - Analyzing the tradeoff between organic content and advertisements. - Investigating the relationship between engagement metrics and monetization strategies. - Assessing the impact of re-pin behaviors on purchase decisions. - Identifying levers to enhance enterprise metrics. - Establish best practices for instrumentation and experimentation, communicating these guidelines to product engineering teams to support Pinterest's mission of inspiring users to create a fulfilling life. - Apply scientific rigor and statistical methods to address challenges in product creation, development, and enhancement, with a focus on understanding user behaviors. - Iteratively build and prototype analysis pipelines to generate insights at scale, while deepening understanding of data structures and metrics. Advocate for necessary changes to support product development. - Collaborate cross-functionally to distill and communicate key insights, working closely with product managers, engineers, designers, and researchers to shape future Pinterest experiences. What We're Looking For: - 7+ years of experience analyzing data in a fast-paced, data-driven environment, demonstrating the ability to apply scientific methods to solve real-world problems using web-scale data. - Extensive background in solving analytical problems using quantitative approaches, including Machine Learning, Statistical Modeling, Forecasting, Econometrics, or related fields. - A commitment to scientific rigor in analysis, with a keen attention to detail, skepticism, and a focus on delivering high-quality, results-oriented output. - Proficiency in machine learning and deep learning frameworks such as PyTorch, TensorFlow, or scikit-learn. - Ability to handle large, complex data sets proficiently, fluency in SQL (or similar database languages), and proficiency in a scripting language like Python or R. - Excellent communication skills, capable of explaining insights to both technical and non-technical stakeholders. - A collaborative mindset, able to partner effectively with cross-functional leadership to translate insights into actionable strategies.