Staff Data Scientist, Ads Performance
Staff Data Scientist, Ads Performance
Job Description
Responsibilities
- Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future
- Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis
- Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth; be a technical leader for junior data scientists
- Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds
- Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation
Qualifications
- 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data
- Direct involvement in the evaluation, refinement, and deployment of ads optimization models for ads delivery systems
- Proficiency in leveraging large datasets for performance analysis and gap identification
- Proven ability to apply scientific methods to solve real-world problems on web-scale data
- Expertise in SQL and Python
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
- Experience leading key technical projects and substantially influencing the scope and output of others
Preferred Qualifications
- Experience in digital ad delivery stacks
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
164,695 - 339,078 USD / yearly
Estimated Salary Rangemedium confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- SQLintermediate
- Pythonintermediate
- Scientific methods on web-scale dataintermediate
- Large dataset analysisintermediate
- Causal inferenceintermediate
- Business and product senseintermediate
- Communication skillsintermediate
- Leadership and mentoringintermediate
- Experimentation and A/B testingintermediate
- Digital ad delivery stacksintermediate
Required Qualifications
- 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data (experience)
- Direct involvement in the evaluation, refinement, and deployment of ads optimization models for ads delivery systems (experience)
- Proficiency in leveraging large datasets for performance analysis and gap identification (experience)
- Proven ability to apply scientific methods to solve real-world problems on web-scale data (experience)
- Expertise in SQL and Python (experience)
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions (experience)
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams (experience)
- Experience leading key technical projects and substantially influencing the scope and output of others (experience)
Preferred Qualifications
- Experience in digital ad delivery stacks (experience)
Responsibilities
- Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future
- Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis
- Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth; be a technical leader for junior data scientists
- Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds
- Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation
Tags & Categories
Staff Data Scientist, Ads Performance
Staff Data Scientist, Ads Performance
Job Description
Responsibilities
- Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future
- Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis
- Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth; be a technical leader for junior data scientists
- Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds
- Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation
Qualifications
- 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data
- Direct involvement in the evaluation, refinement, and deployment of ads optimization models for ads delivery systems
- Proficiency in leveraging large datasets for performance analysis and gap identification
- Proven ability to apply scientific methods to solve real-world problems on web-scale data
- Expertise in SQL and Python
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
- Experience leading key technical projects and substantially influencing the scope and output of others
Preferred Qualifications
- Experience in digital ad delivery stacks
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
164,695 - 339,078 USD / yearly
Estimated Salary Rangemedium confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- SQLintermediate
- Pythonintermediate
- Scientific methods on web-scale dataintermediate
- Large dataset analysisintermediate
- Causal inferenceintermediate
- Business and product senseintermediate
- Communication skillsintermediate
- Leadership and mentoringintermediate
- Experimentation and A/B testingintermediate
- Digital ad delivery stacksintermediate
Required Qualifications
- 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data (experience)
- Direct involvement in the evaluation, refinement, and deployment of ads optimization models for ads delivery systems (experience)
- Proficiency in leveraging large datasets for performance analysis and gap identification (experience)
- Proven ability to apply scientific methods to solve real-world problems on web-scale data (experience)
- Expertise in SQL and Python (experience)
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions (experience)
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams (experience)
- Experience leading key technical projects and substantially influencing the scope and output of others (experience)
Preferred Qualifications
- Experience in digital ad delivery stacks (experience)
Responsibilities
- Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future
- Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis
- Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth; be a technical leader for junior data scientists
- Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds
- Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation
Tags & Categories