Data Scientist
Common Sense Media
San Francisco, CA, US
Onsite
2026-06-25
Announced salary
$140k–$166k
Low
$113K
Median
$149K
High
$196K
Market in San Francisco · BLS OEWS 2025
Job description
**Data Scientist**
**Organization**
Common Sense Media
**Department**
Data
**Reports To**
Senior Director, Data \& Analytics
**Location**
San Francisco, CA
**Classification**
**Salary Range**
Full\-time, Exempt
$140,00–$166,250
**POSITION OVERVIEW**
Common Sense Media is seeking a Data Scientist to help build data capabilities that allows the organization to answer the questions that matter most to advancing our mission and driving impact for kids and families. This is a hands\-on, full\-stack individual contributor role responsible for developing pipelines, models, and analyses that turn data from across the Common Sense Media ecosystem into reliable, decision\-ready insights.
The Data Scientist will develop predictive and statistical models that support organization\-wide decisions, design and analyze experiments, apply causal inference methods, and lead impact analyses that measure how Common Sense Media's work affects kids, families, and educators, translating findings into clear, actionable recommendations for both technical and non\-technical audiences. The Data Scientist's work will span the full range of data science at Common Sense Media, from foundational data engineering and data modeling through analytics, machine learning, experimentation, and impact analysis.
As a senior technical voice on the team, the Data Scientist will help uplevel the organization's capabilities in data science, machine learning, and generative AI, advising on methodology, helping to develop and test AI product features, and raising the technical bar within product and engineering.
**KEY RESPONSIBILITIES**
*Analytics \& Modeling*
* Conduct rigorous exploratory and descriptive analyses that establish the foundational understanding of our audiences, programs, and performance.
* Develop predictive and statistical models that support organization\-wide decisions.
* Apply modern machine learning techniques to ship models and ana
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