Staff Data Scientist, Curation Ecosystem
Staff Data Scientist, Curation Ecosystem
Job Description
Responsibilities
- Build a deeper understanding of our Pinterest Curation ecosystem; understanding and quantifying the opportunities and Pinner needs around boards, trends, collages, and more
- Develop robust frameworks, combining online and offline methods, to comprehensively understand the outputs of our recommendations
- Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners
- Work cross-functionally to build relationships, proactively communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest
- Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process
- Mentor and up-level junior data scientists on the team
Qualifications
- 7+ 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
- Strong interest and experience in recommendation systems and causal inference
- Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark)
- Ability to work independently and drive your own projects
- Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners
- A team player eager to partner with cross-functional partners to quickly turn insights into actions
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
163,064 - 335,720 USD / yearly
Estimated Salary Rangemedium confidence
180,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Scientific methods for real-world problems on web-scale dataintermediate
- Recommendation systemsintermediate
- Causal inferenceintermediate
- Quantitative programming (Python/R)intermediate
- Data manipulation (SQL/Spark)intermediate
- Statistical methodsintermediate
- Communication skills for technical and non-technical audiencesintermediate
Required Qualifications
- 7+ 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 (experience)
- Strong interest and experience in recommendation systems and causal inference (experience)
- Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark) (experience)
- Ability to work independently and drive your own projects (experience)
- Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners (experience)
- A team player eager to partner with cross-functional partners to quickly turn insights into actions (experience)
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience (experience)
Responsibilities
- Build a deeper understanding of our Pinterest Curation ecosystem; understanding and quantifying the opportunities and Pinner needs around boards, trends, collages, and more
- Develop robust frameworks, combining online and offline methods, to comprehensively understand the outputs of our recommendations
- Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners
- Work cross-functionally to build relationships, proactively communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest
- Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process
- Mentor and up-level junior data scientists on the team
Tags & Categories
Staff Data Scientist, Curation Ecosystem
Staff Data Scientist, Curation Ecosystem
Job Description
Responsibilities
- Build a deeper understanding of our Pinterest Curation ecosystem; understanding and quantifying the opportunities and Pinner needs around boards, trends, collages, and more
- Develop robust frameworks, combining online and offline methods, to comprehensively understand the outputs of our recommendations
- Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners
- Work cross-functionally to build relationships, proactively communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest
- Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process
- Mentor and up-level junior data scientists on the team
Qualifications
- 7+ 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
- Strong interest and experience in recommendation systems and causal inference
- Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark)
- Ability to work independently and drive your own projects
- Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners
- A team player eager to partner with cross-functional partners to quickly turn insights into actions
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
163,064 - 335,720 USD / yearly
Estimated Salary Rangemedium confidence
180,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Scientific methods for real-world problems on web-scale dataintermediate
- Recommendation systemsintermediate
- Causal inferenceintermediate
- Quantitative programming (Python/R)intermediate
- Data manipulation (SQL/Spark)intermediate
- Statistical methodsintermediate
- Communication skills for technical and non-technical audiencesintermediate
Required Qualifications
- 7+ 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 (experience)
- Strong interest and experience in recommendation systems and causal inference (experience)
- Strong quantitative programming (Python/R) and data manipulation skills (SQL/Spark) (experience)
- Ability to work independently and drive your own projects (experience)
- Excellent written and communication skills, and able to explain learnings to both technical and non-technical partners (experience)
- A team player eager to partner with cross-functional partners to quickly turn insights into actions (experience)
- Bachelor’s/Master’s degree in a relevant field such as computer science, or equivalent experience (experience)
Responsibilities
- Build a deeper understanding of our Pinterest Curation ecosystem; understanding and quantifying the opportunities and Pinner needs around boards, trends, collages, and more
- Develop robust frameworks, combining online and offline methods, to comprehensively understand the outputs of our recommendations
- Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners
- Work cross-functionally to build relationships, proactively communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest
- Relentlessly focus on impact, whether through influencing product strategy, advancing our north star metrics, or improving a critical process
- Mentor and up-level junior data scientists on the team
Tags & Categories