This role pays more than
89%
of similar roles. Most pay
$127,991–$223,430
— the shaded band above.
At the midpoint, this role pays about
$252k
versus about
$176k
for comparable roles.
Based on 240 similar postings.
Employer
About Pinterest
Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.
Pinterest currently has
27 open roles
on FindRole.
Listed pay typically runs
$177,185–$339,078
across 27 roles with salary data.
As the Staff Data Scientist, Forecasting, you will serve as the technical lead for the forecasting team, owning the strategy and implementation of models for key company metrics like monthly active users. You will manage the full modeling lifecycle, including feature engineering, prototyping, deployment, and monitoring, while defining model architectures and standards in partnership with Engineering. The role involves translating complex forecasts into actionable insights for senior leadership and driving broader time-series impacts such as anomaly detection and root-cause analysis. You will mentor at least two data scientists to improve technical quality. Required skills include expertise in Python, SQL (Hive/Presto/Spark), and Airflow. You must possess a strong background in applied statistics, econometrics, and time-series modeling to solve complex business problems using web-scale data to inform strategic planning and executive decision-making.
What does a Data Scientist earn in California?
Median $211329 from 80 postings across 29 companies.
Serve as the technical lead for the forecasting team to own strategy and implementation of key metric models.
Manage the full modeling lifecycle including feature engineering, development, deployment, monitoring, and explainability.
Define the technical vision for model architectures and partner with Engineering to build scalable forecasting platforms.
Present scenario analyses and recommendation frameworks to senior leadership to inform executive decision-making.
Develop advanced time-series capabilities such as anomaly detection, root-cause analysis, and campaign attribution.
Integrate forecasting insights into the operational rhythms of BizOps, Finance, and product teams.
Mentor and lead a team of data scientists by providing technical guidance and performance coaching.
What we're looking for
8+ years of combined post-graduate academic and industry experience building and shipping production time-series/forecasting models with web-scale data.
Proven track record of delivering adjustable, well-calibrated, and explainable forecasting systems to inform decision-making.
Strong background in time-series modeling and applied statistics or econometrics.
Advanced degree (MS or PhD) preferred.
Expertise in at least one scripting language, ideally Python.
Strong SQL skills and experience building reliable data pipelines using tools like Airflow.
Proven technical leadership success leading critical projects and influencing the scope of other contributors.
Excellent communication skills to distill complex analyses into concise narratives for executive audiences.
Machine Learning
Artificial Intelligence
Natural Language Processing
Python
R
SQL
NoSQL
Plotly
Seaborn
ggplot2
Data Mining
Data Visualization
Text Mining