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# Data Scientist

- **Company:** The Meta Game, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $177,000.0 - $247,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Computer Engineering, Query Languages, Python (Programming Language), Mathematical Software, SQL Databases, Scripting, Multi-Agent Systems, Prompt Engineering, Model Validation, Information Technology
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_a888f68b12ea2b9761cd03c8077c93f7

## About the Role

* Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or Statistics (or equivalent practical experience).
 * Minimum 6 years of work experience in analytics (minimum 4 years with a Ph.D.).
 * Experience with data querying languages such as SQL, scripting languages such as Python, and/or statistical or mathematical software such as R., * Experience in frontier AI products or risks, including navigating online adversarial environments in Trust & Safety or Fraud/Risk/Security contexts, including model evals, threat modeling, actor telemetry, and human-in-the-loop review systems.
 * Comfort working in fast-paced, high-ambiguity, cross-functional environments, including explaining risk dimensions clearly to policy stakeholders.
 * Background working with ambiguous and sparse data to operationalize harm prevalence measurement, causal inference, and root-cause analysis, supported by strong quantitative and statistical foundations.
 * Master's or Ph.D. degree in a quantitative field.
 * Experience implementing responsible and ethical AI practices such as risk assessment, bias mitigation, and quality and accuracy reviews.
 * Demonstrated ability to integrate AI tools to optimize or redesign workflows and deliver measurable impact, such as efficiency or quality improvements.
 * Demonstrated ongoing AI skill development, including prompt/context engineering and agent orchestration, and staying current with emerging AI technologies.

## Description

* Measure abuse and harms: develop statistical telemetry and measurement frameworks to detect, monitor, and understand policy violations or emergent harms.
 * Scale model evaluation: create a scalable evaluation framework that adapts to changing agentic model capabilities and the safety or risk landscape, grounded in statistics.
 * Evaluate safeguards: scale offline and online performance evaluation of safeguards using human-in-the-loop methods and active learning.
 * Design experiments and analyses: run controlled experiments and rollouts to measure the impact of policy or risk definition changes and safety mitigations.
 * Build reporting and intelligence: develop signals, pipelines, dashboards, and real-time monitoring mechanisms to support interventions and safety planning.