Data Scientist

COMMON SENSE MEDIA • San Francisco, CA

1d • $140,000 - $166,250 • Onsite

About The Position

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.

Requirements

• 8+ years of experience in applied data science, analytics, or a closely related quantitative field, with a track record of shipping models and analyses that have changed decisions.
• Strong hands-on skills in SQL and Python or R, and expert use of standard machine learning libraries.
• Experience building and maintaining production data pipelines using modern cloud data warehouses (Snowflake, BigQuery, or Redshift) and modern data stack tooling (dbt, Airflow, Fivetran, or equivalents).
• Demonstrated experience designing and analyzing experiments, including A/B tests, quasi-experiments, and causal inference methods.
• Experience leading rigorous impact or program evaluation that measures real-world outcomes.
• Experience mentoring junior data scientists.
• Excellent written and verbal communication skills, with the ability to translate technical work into clear narratives for both technical and non-technical audiences.
• Demonstrated ability to serve as a senior technical voice within an organization, raising the technical bar of teammates and helping non-technical colleagues use data and AI tools effectively in their work.
• Strong understanding of data governance, privacy, and responsible data and AI practices, with particular sensitivity to data involving children and families.

Nice To Haves

• Familiarity with product analytics, CRM, and marketing platforms (Amplitude, Google Analytics, Salesforce, Braze) and their underlying data structures is a plus.
• Experience building predictive models for subscription, retention, lifetime value, or similar member or customer lifecycle problems is a plus.
• Experience implementing and evaluating generative AI or LLM-based solutions, including prompt engineering, fine-tuning, retrieval-augmented generation, or self-hosted models, with rigorous evaluation against human or ground-truth baselines, is a plus.
• Experience designing AI evaluation frameworks, including human-in-the-loop evaluation, bias and fairness assessment, and ongoing monitoring of model performance, is a plus.
• Prior experience in a mission-driven, nonprofit, education, or media organization is a plus.

Responsibilities

• 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 analyses that drive impact.
• Design and execute A/B tests and randomized controlled trials.
• Leverage rigorous quasi-experimental designs (e.g., difference-in-differences, regression discontinuity) and advanced causal inference techniques to evaluate the impact of complex product and program decisions where randomized testing is not feasible.
• Lead rigorous impact analyses and program evaluations that measure how Common Sense Media's work affects kids, families, and educators.
• Apply causal inference and evaluation methods to measure real-world outcomes.
• Translate findings into clear, actionable recommendations for both technical and non-technical audiences.
• Partner closely with colleagues across Common Sense Media to put data to work across the organization.
• Own the data models that turn raw data into clean, reliable, analysis-ready data sets used across the organization.
• Work with internal teams and external partners to establish data collection approaches, integrate new data sources, and ensure that incoming data is structured and trustworthy.
• Build and maintain the data pipelines and transformations necessary to support modeling, reporting, and impact measurement.
• Serve as a senior technical voice on the team, advising on methodology and raising the technical bar around how to use data in thoughtful decision-making.
• Help uplevel the organization's capabilities in data science, machine learning, and generative AI, supporting the development and testing of AI tools and features across the organization.

Benefits

• Competitive nonprofit compensation and comprehensive benefits.
• A collaborative, flexible work environment with meaningful leadership access and visibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed