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# Data Scientist, Meta Superintelligence Labs (Safety)

- **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, Computer Engineering, Query Languages, Python (Programming Language), Mathematical Software, SQL Databases, Scripting, Prompt Engineering, Model Validation, Information Technology, Human in the Loop
- **Published:** October 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f4da8d3d5de68071

## About the Role

* Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 * Bachelor's degree in Mathematics, Statistics, Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 * A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.)
 * Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R), * Experience in frontier AI products or risks, and navigating online, adversarial environments in Trust & Safety or Fraud/Risk/Security domains. Model evals, threat modelling, actor telemetry, human-in-the-loop review systems don't sound foreign to you
 * Familiar with fast-paced, high-ambiguity, cross-functional environments - able to jump from agentic trace deep-dives to explaining risk dimensions in plain English to policy stakeholders
 * Background in ambiguous and sparse data environments to operationalize e.g. harm prevalence measurement, causal inference, root-cause analysis- rooted in strong quantitative/statistical foundations
 * Master's or Ph.D. Degree in a quantitative field
 * Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 * Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 * Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

## Description

* Measure abuse: build statistical telemetry and measurement frameworks to detect and monitor policy violations or emergent harms
 * Scale model evaluation: design a scalable framework adapting to evolving agentic model capabilities and safety/risk landscape, grounded in statistics
 * Evaluate and optimize safeguards: scale offline and online performance evaluation of our safeguards using human-in-the-loop and active learning
 * Design experiments and analyses: Conduct controlled experiments and rollouts to evaluate the impact of policy or risk definition changes and safety mitigations
 * Build intelligence and reporting: build signals, pipelines, dashboards to enable real-time monitoring driving interventions and safety roadmaps