Remote opportunity at
Reddit, Inc.Senior Data Scientist, Safety Enforcement
Reddit operates a massive online platform consisting of over 100,000 active communities and approximately 130 million daily active unique visitors where individuals share content, vote, and…
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About This Role
Reddit operates a massive online platform consisting of over 100,000 active communities and approximately 130 million daily active unique visitors where individuals share content, vote, and engage in conversations. To maintain platform safety and trust, the organization is seeking a Senior Data Scientist for its Safety Enforcement team. This position can be performed remotely within the United States, with optional access to physical offices located in San Francisco, Los Angeles,…
Job Description
Reddit operates a massive online platform consisting of over 100,000 active communities and approximately 130 million daily active unique visitors where individuals share content, vote, and engage in conversations. To maintain platform safety and trust, the organization is seeking a Senior Data Scientist for its Safety Enforcement team. This position can be performed remotely within the United States, with optional access to physical offices located in San Francisco, Los Angeles, New York City, and Chicago. The safety organization functions as a closed-loop structure, where Safety Enforcement Data Scientist professionals design and refine the models, rules, and systems needed to address and mitigate abuse fairly and efficiently.
This individual will take ownership of specific enforcement problem areas, turning ambiguous risks and written policies into actionable signals, labels, detection strategies, and evaluation frameworks. Daily duties include investigating adversarial activity, prototyping models and rules, establishing decision thresholds, diagnosing enforcement gaps, and monitoring deployed systems. This hands-on position also involves integrating modern artificial intelligence methods, such as language models, to enhance detection and operational workflows with adequate human oversight. Candidates should note that the job may involve exposure to sensitive material as well as participation in an incident-response on-call rotation requiring occasional after-hours work.
Responsibilities
- Manage the complete enforcement lifecycle from problem framing and signal discovery to rollout, monitoring, and iteration
- Analyze large-scale behavioral, content, account, and network data to uncover adversarial patterns and emerging threats
- Develop models, classifiers, scoring systems, rules, and analytical prototypes utilizing statistical, machine-learning, or generative AI techniques
- Establish evaluation frameworks addressing precision, recall, calibration, coverage, robustness, fairness, and operational costs
- Collaborate with engineering and machine learning partners to operationalize detection approaches, establish logging needs, and define rollback criteria
- Translate written policies and product requirements into modelable targets, labels, decision rules, and reviewer workflows
- Design staged rollouts, experiments, and observational analyses to test interventions against harm while controlling false positives
- Participate in urgent escalations, conduct post-incident analyses, and convert findings into long-term detection improvements
- Build reusable datasets, evaluation harnesses, and monitoring tools while communicating recommendations and mentoring junior peers
Requirements
- Ph.D. with 4 or more years of relevant industry experience, or a Master’s degree with 8 or more years of relevant industry experience in Data Science, Applied Science, Economics, Statistics, Computer Science, Operations Research, or a related quantitative field
- Applied experience working in safety, enforcement engineering, fraud, or similar fast-paced and adversarial domains with incomplete or evolving data
- Proficiency in SQL and Python to write production-grade analytical code and contribute to data pipelines
- Background in statistical analysis, experiment design, causal modeling, and machine learning techniques including classification, ranking, and anomaly detection
- Practical understanding of evaluating real-world decision systems, encompassing sampling, label quality, class imbalance, precision and recall, and calibration
- Ability to break down ambiguous problems into manageable components and collaborate effectively with product, engineering, operations, and policy teams
- Communication skills necessary to convey complex technical concepts and tradeoffs to both technical and non-technical stakeholders
Qualifications
- Experience in Trust and Safety, integrity, fraud, spam and abuse, account security, cybersecurity, risk, content moderation, or related adversarial spaces
- Familiarity with enforcement-relevant methods such as graph or network analysis, natural language processing, embeddings, or behavioral modeling
- Background in applying language models to detection, investigations, labeling, or reviewer assistance while measuring operational tradeoffs
- Experience partnering with engineers to launch and monitor production models or rules, including post-launch tuning and incident response
- Experience designing prioritization or triage systems for human review operations
- Experience assessing fairness, bias, privacy, and policy-aware tradeoffs in automated decision systems
Core Skills
Benefits
- Comprehensive healthcare benefits and income replacement programs
- 401(k) program with employer match
- Global benefit programs covering workspace, professional development, and caregiving support
- Family planning support and gender-affirming care
- Mental health and coaching benefits
- Flexible vacation and paid volunteer time off
- Generous paid parental leave
- Equity in the form of restricted stock units
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Where is this job located?
This position is completely remote-friendly within the United States. Employees who live near physical offices in San Francisco, Los Angeles, New York City, or Chicago may also work from those offices as often as they wish.
What is the salary range for this position?
The base salary range for this role is USD 190,800 to 267,100 per year, and the position is also eligible to receive equity in the form of restricted stock units.
What are the core educational and experience requirements?
Candidates must hold either a Ph.D. with at least 4 years of relevant industry experience or a Master’s degree with at least 8 years of relevant industry experience in Data Science, Applied Science, Economics, Statistics, Computer Science, Operations Research, or a related quantitative field.
Does this role involve handling sensitive material or irregular hours?
Yes, the posting notes that the role may involve exposure to sensitive content and requires participation in an incident-response on-call rotation, which can include occasional work outside normal hours.
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