Director of Data Science, Trust & Safety, Signals and Content Understanding

Job Location:

San Francisco, CA - USA

Monthly Salary: Not Disclosed

Posted on: 16 hours ago

Vacancies: 1 Vacancy

Job Summary

This is a pivotal Director-level leadership role with the opportunity to strengthen the foundations of trust on Pinterest while advancing how we understand Pinners and content at scale. You will lead a high-impact data science organization and partner deeply with Product Engineering and Policy to build and operate the next generation of integrity user understanding and content understanding systems that power enforcement and distribution decisions across the core mandate is to evolve the organization from reactive moderation and lagging harm reporting into a proactive metrics-driven operating systemwhere we manage leading indicators that predict risk improve understanding quality and keep Pinterest safe inspiring and useful.

What youll do:

Set Strategy & Roadmap: Define the multi-year vision and priorities across Trust & Safety User Understanding and Content Understandingestablishing north-star outcomes (e.g. prevalence & reach reduction user trust ecosystem health content quality user and content understanding) and the leading indicators that drive them.
Operationalize Leading Indicators: Identify instrument and build operating cadences around key input metrics that influence integrity and understandingsuch as policy risk signals spam/abuse rates account authenticity coverage and latency precision/recall of enforcement appeal overturn rates content quality signals and user feedback/friction signals.
Lead a Talented Organization: Hire develop and inspire a world-class team of data science managers and senior ICs spanning product analytics ML evaluation experimentation causal inference and integrity measurement.
Partner to Ship Impact: Work hand-in-hand with Product Engineering and Policy teams to deliver end-to-end improvements across detection enforcement precision and distribution systemstranslating ambiguous trust and understanding questions into shipped product/ML capabilities with measurable impact.
Elevate Measurement & Decision Quality: Own measurement strategy for safety integrity and understanding quality employing causal inference experimentation offline evaluation and long-term value measurement to quantify trade-offs and reduce unintended consequences.
Communicate and Align Across Stakeholders: Present complex analyses and recommendations to executives and cross-functional partners driving alignment on difficult trade-offs between safety expression growth and product usability.

What were looking for:

MS or PhD in a quantitative field or equivalent experience.
10 years in Data Science Algorithmic Engineering or ML with significant impact in digital advertising or large-scale marketplaces.
5 years of managing data science organizations including managing managers.
Deep experience with:

Statistical analysis causal inference and experiment design for complex marketplaces.
Production analytics and large-scale data tooling (Python/R SQL Spark/Hive).
Applied ML or relevance/ranking systems; familiarity with auction dynamics pacing and quality modeling.

Proven ability to operate through input metrics tied to business outcomes.
Excellent communication and influencing skills.

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 1-2 times/quarter and therefore can be situated anywhere in the country.

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:

Director

What youll do:

Set Strategy & Roadmap: Define the multi-year vision and priorities across Trust & Safety User Understanding and Content Understandingestablishing north-star outcomes (e.g. prevalence & reach reduction user trust ecosystem health content quality user and content understanding) and the leading indicators that drive them.
Operationalize Leading Indicators: Identify instrument and build operating cadences around key input metrics that influence integrity and understandingsuch as policy risk signals spam/abuse rates account authenticity coverage and latency precision/recall of enforcement appeal overturn rates content quality signals and user feedback/friction signals.
Lead a Talented Organization: Hire develop and inspire a world-class team of data science managers and senior ICs spanning product analytics ML evaluation experimentation causal inference and integrity measurement.
Partner to Ship Impact: Work hand-in-hand with Product Engineering and Policy teams to deliver end-to-end improvements across detection enforcement precision and distribution systemstranslating ambiguous trust and understanding questions into shipped product/ML capabilities with measurable impact.
Elevate Measurement & Decision Quality: Own measurement strategy for safety integrity and understanding quality employing causal inference experimentation offline evaluation and long-term value measurement to quantify trade-offs and reduce unintended consequences.
Communicate and Align Across Stakeholders: Present complex analyses and recommendations to executives and cross-functional partners driving alignment on difficult trade-offs between safety expression growth and product usability.

What were looking for:

MS or PhD in a quantitative field or equivalent experience.
10 years in Data Science Algorithmic Engineering or ML with significant impact in digital advertising or large-scale marketplaces.
5 years of managing data science organizations including managing managers.
Deep experience with:

Statistical analysis causal inference and experiment design for complex marketplaces.
Production analytics and large-scale data tooling (Python/R SQL Spark/Hive).
Applied ML or relevance/ranking systems; familiarity with auction dynamics pacing and quality modeling.

Proven ability to operate through input metrics tied to business outcomes.
Excellent communication and influencing skills.

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 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement: