Staff Data Scientist, Ad Measurement Products

Job Location:

San Francisco, CA - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

About Pinterest:

Millions of people around the world come to our platform to find creative ideas dream about new possibilities and plan for memories that will last a lifetime. At Pinterest were on a mission to bring everyone the inspiration to create a life they love and that starts with the people behind the product.

Discover a career where you ignite innovation for millions transform passion into growth opportunities celebrate each others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well explore your foundational skills and how you collaborate with AI.

Through our interview process what matters most is that you can always explain your approach showing us not just what you know but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Were looking for a Staff Data Scientist to lead the science behind how advertisers understand the impact of their investment on Pinterest through first and third party measurement products. Youll push the boundaries of ads measurement advancing our approaches to causal inference and incrementality and partner closely with Product and Engineering as well as represent Pinterest science externally with customers and partners.

What youll do

Design implement and validate advanced causal inference methods for incrementality and lift measurement.
Apply AI/ML techniques and AI-assisted workflows to improve the scale speed and quality of ads measurement experimentation and insight generation across first- and third-party measurement products.
Ensure scientific rigor in our measurement products by anticipating and mitigating risks such as bias imbalance under-power and data quality issues including those that may arise from AI-enabled systems.
Influence Ads Product and Engineering to define the measurement roadmap and integrate science and AI-powered solutions into products and platforms including model-driven diagnostics anomaly detection automated insight generation and decision-support for advertisers.
Collaborate with internal and external measurement partners such as clean rooms conversion APIs MMM partners and MTA vendors to design and evaluate joint solutions.
Define and own key success metrics for first-party measurement products; build tools and frameworks that enable teams and advertisers to make better decisions.
Provide technical leadership and mentorship to other data scientists and analysts elevating measurement rigor and impact across the org.
Clearly communicate complex concepts and tradeoffs to executives cross-functional stakeholders external customers and partners including the opportunities and limitations of AI-based approaches.

What were looking for

8 years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
5 years in ads measurement with a strong focus on ad effectiveness and incrementality (e.g. conversion lift brand lift budget-split testing matched-market tests MMM MTA).
Proficiency in SQL and expertise in at least one scripting language (ideally Python or R).
Strong business and product sense with a track record of turning ambiguous questions into well-defined analyses or success metrics and driving decisions that balance scientific rigor and business value.
Experience applying AI/ML methods or AI-assisted workflows to analytics experimentation measurement or product problems.
Strong judgment in evaluating AI-generated outputs and translating them into reliable explainable and scientifically sound solutions.
Demonstrated leadership of key technical projects and meaningful influence on the work of other data scientists particularly junior and senior peers.
Excellent communication skills and experience leading initiatives across multiple product areas and partnering with leadership and cross-functional teams.

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means were 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 times per week and therefore needs to be in a commutable distance from one of the following offices San Francisco Palo Alto or Seattle.

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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Required Experience:

Staff IC

About Pinterest:Millions of people around the world come to our platform to find creative ideas dream about new possibilities and plan for memories that will last a lifetime. At Pinterest were on a mission to bring everyone the inspiration to create a life they love and that starts with the people b...

About Pinterest:

What youll do

Design implement and validate advanced causal inference methods for incrementality and lift measurement.
Apply AI/ML techniques and AI-assisted workflows to improve the scale speed and quality of ads measurement experimentation and insight generation across first- and third-party measurement products.
Ensure scientific rigor in our measurement products by anticipating and mitigating risks such as bias imbalance under-power and data quality issues including those that may arise from AI-enabled systems.
Influence Ads Product and Engineering to define the measurement roadmap and integrate science and AI-powered solutions into products and platforms including model-driven diagnostics anomaly detection automated insight generation and decision-support for advertisers.
Collaborate with internal and external measurement partners such as clean rooms conversion APIs MMM partners and MTA vendors to design and evaluate joint solutions.
Define and own key success metrics for first-party measurement products; build tools and frameworks that enable teams and advertisers to make better decisions.
Provide technical leadership and mentorship to other data scientists and analysts elevating measurement rigor and impact across the org.
Clearly communicate complex concepts and tradeoffs to executives cross-functional stakeholders external customers and partners including the opportunities and limitations of AI-based approaches.

What were looking for

8 years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
5 years in ads measurement with a strong focus on ad effectiveness and incrementality (e.g. conversion lift brand lift budget-split testing matched-market tests MMM MTA).
Proficiency in SQL and expertise in at least one scripting language (ideally Python or R).
Strong business and product sense with a track record of turning ambiguous questions into well-defined analyses or success metrics and driving decisions that balance scientific rigor and business value.
Experience applying AI/ML methods or AI-assisted workflows to analytics experimentation measurement or product problems.
Strong judgment in evaluating AI-generated outputs and translating them into reliable explainable and scientifically sound solutions.
Demonstrated leadership of key technical projects and meaningful influence on the work of other data scientists particularly junior and senior peers.
Excellent communication skills and experience leading initiatives across multiple product areas and partnering with leadership and cross-functional teams.

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means were 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 times per week and therefore needs to be in a commutable distance from one of the following offices San Francisco Palo Alto or Seattle.

Relocation Statement: