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Staff Data Scientist, Ads Market Design
Company | |
Address | Palo Alto, CA, United States |
Employment type | FULL_TIME |
Salary | |
Category | IT Services and IT Consulting,Software Development,Technology, Information and Internet |
Expires | 2023-08-05 |
Posted at | 10 months ago |
2550219
- Opportunity sizing and analysis. Should Pinterest lower the floor price in the bidding? Write clear, actionable analyses that help teams identify areas of improvement and investment.
- Deep strategic analysis to answer core questions such as: How do we assess the trade-off between metrics change, such as revenue and engagement? How should we evaluate overall impact from changes in one side of the marketplace?
- Leadership: Lead and mentor the scope of work for data scientists in the same area, demonstrating high-quality output of both yourself and others for whom you are responsible. Provide continuous and candid feedback, recognizing individual strengths and contributions and flagging opportunities to improve performance.
- Modeling: Build LTV models to assess long-term value in support of product launches, including design of success metrics and key features and evaluation strategy.
- Creating and tracking success metrics. Identify the right measures of success for engineering teams and help them track those metrics. Break down high-level metrics into actionable segments. This work may span from collecting entirely new datasets to building dashboards to track components of a metric (e.g., monitoring conversion data for missing values, implausible values, duplicated data, etc. by advertiser over time).
- Improve decision velocity and quality using data scientist tool kit: experimentation, causal inference techniques, etc. Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis etc.
- Strong impact-driven mindset: a track record of making things happen.
- Experience leading key technical projects and substantially influencing the scope and output of others.
- Proficiency in SQL/Hive and at least one scripting language(ideally Python/R).
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
- Strong focus on understanding in two-sided marketplace.
- Proven ability to apply scientific methods to solve real-world problems on web-scale data.
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
- 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
- Experience in the strategic analytics side of data science: shaping decisions rather than just building models.
- Statistical rigor. Can consult with the team and others on statistically valid approaches to problems.
- Familiarity with online experimentation and its pitfalls.
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