Staff Data Scientist - Trust and Safety
To see similar active jobs please follow this link: Remote Development jobs
We are seeking a skilled Staff Data Scientist to enhance measurement on Trust and Safety within our organization. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and up-level our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world.
What you’ll do
Develop a basket of metrics to measure overall health of Pinterest Trust and Safety Platform
Develop a framework to quantify aggregated incurred harm for unsafe categories such as Adult Content, Self Harm, Misinformation, Hate Speech etc
Research and develop methodology to improve statistical power of existing metrics and experimentation
Drive launch review process, define launching criteria for Trust and Safety experiments
Adopt LLM and other state of art techniques to apply on Trust & Safety use cases
What we’re looking for
10+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data
Extensive experience solving measurement problems using quantitative approaches including in the fields of Statistical, Econometrics, Optimization, Machine Learnings or other related fields
A scientifically rigorous approach to analysis and data, and a well-tuned sense of skepticism, attention to detail and commitment to high-quality, results-oriented output
Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R)
Excellent communication skills and ability to explain learnings to both technical and non-technical partners
This position is not eligible for relocation assistance.
#LI-NM4 or #LI-REMOTE
About the job
Staff Data Scientist - Trust and Safety
To see similar active jobs please follow this link: Remote Development jobs
We are seeking a skilled Staff Data Scientist to enhance measurement on Trust and Safety within our organization. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and up-level our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world.
What you’ll do
Develop a basket of metrics to measure overall health of Pinterest Trust and Safety Platform
Develop a framework to quantify aggregated incurred harm for unsafe categories such as Adult Content, Self Harm, Misinformation, Hate Speech etc
Research and develop methodology to improve statistical power of existing metrics and experimentation
Drive launch review process, define launching criteria for Trust and Safety experiments
Adopt LLM and other state of art techniques to apply on Trust & Safety use cases
What we’re looking for
10+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data
Extensive experience solving measurement problems using quantitative approaches including in the fields of Statistical, Econometrics, Optimization, Machine Learnings or other related fields
A scientifically rigorous approach to analysis and data, and a well-tuned sense of skepticism, attention to detail and commitment to high-quality, results-oriented output
Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R)
Excellent communication skills and ability to explain learnings to both technical and non-technical partners
This position is not eligible for relocation assistance.
#LI-NM4 or #LI-REMOTE