Staff Data Scientist, Ads Product
Staff Data Scientist driving ads product strategy and data-driven decision-making at Pinterest. Partners with product, engineering, and finance teams to translate business questions into analytical solutions and maintain data quality.
About the job
What you'll do
- Drive Ads Product Strategy across Pinterest: Leverage your strong business and product acumen to proactively identify opportunities, generate insights, and drive data-driven decision-making aligned with the organization's strategic objectives. You'll play a crucial role in ensuring data insights inform downstream ML applications and broader product improvements.
- Translate Complex Business Needs into Data Solutions: Partner closely with product, engineering, and business stakeholders to deeply understand their challenges. You will expertly translate ambiguous business questions into structured analytical problems, providing the "why" and "how" behind performance and identifying new opportunities.
- Ensure Data Trustworthiness and Quality: Establish and uphold high standards for data integrity, consistency, and reliability in all analytical outputs. You will be responsible for ensuring consistently trustworthy and high-quality analyses that directly influence strategic and operational decisions.
- Be a Strategic Thought Partner: Bring proactive and influential product leadership into areas where data-driven decisions and insights are essential for success. This involves acting as a key advisor to Product Managers, Engineering leaders, and other cross-functional partners, anticipating future product needs, and identifying the most impactful questions that data can answer. You will be responsible for defining the analytical roadmap, translating high-level business problems into specific, actionable data initiatives, and guiding the team to execute them effectively to drive significant product and business outcomes.
- Connect Financial & Product Performance: Serve as a key liaison with BizOps, Finance, and other Strategy teams, expertly connecting revenue performance data with product actions and performance metrics to provide a holistic understanding of our business impact and growth drivers.
- Communicate for Impact: Articulate complex data findings, strategic insights, and recommendations clearly and concisely to both technical and non-technical senior stakeholders, influencing business strategy and outcomes.
- Elevate Data Science Practices: Act as a subject matter expert for the broader Data Science team, sharing best practices in data analysis, strategic thinking, and effective communication. You will contribute to a culture of continuous learning and data excellence across the organization.
What we're looking for
- Bachelor’s/Master’s degree in a quantitative field such as Data Science, Statistics, Economics, Business Analytics, or equivalent practical experience.
- 8+ years of combined post-graduate academic and industry experience applying advanced analytical methods to solve complex, real-world business problems on large-scale data, preferably within a fast-paced tech environment.
- Exceptional business acumen and product sense, with a proven ability to translate strategic questions into analytical frameworks and actionable recommendations.
- Understanding of the ads ecosystem, monetization mechanics, and/or real-time bidding, with a strong interest in the financial aspects of these domains.
- Expertise in data democratization principles, including experience designing and maintaining foundational datasets and building comprehensive business intelligence solutions.
- Strong fundamentals in statistics and experimentation, with the ability to interpret and apply insights from various causal inference techniques.
- Proven ability to influence cross-functional partners and senior leadership through compelling data narratives and strategic insights.
- Proficiency in SQL, Python, and experience with data visualization tools (e.g., Tableau, Looker) is required.
Skills
SQL, Python, Tableau, Looker, Statistics, Experimentation, Causal Inference, Data Visualization, Business Intelligence, Data Democratization
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