Senior Data Scientist, Safety Enforcement
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Job Description
Senior Data Scientist building Reddit safety-enforcement models and decision systems against abuse. Analyzing adversarial behavior and partnering across Product, Engineering, Policy, and Operations.
Responsibilities:
- Own one or more defined enforcement problem areas from problem framing and signal discovery through labeling, taxonomy, model or rule development, thresholding, rollout, monitoring, and iteration
- Analyze large-scale behavioral, content, account, and network data to identify adversarial patterns, emerging threats, and mitigation gaps
- Develop models, classifiers, scoring systems, rules, and analytical prototypes using statistical, machine-learning, or GenAI methods
- Create evaluation frameworks addressing precision, recall, calibration, coverage, robustness, fairness, user friction, reviewer capacity, and operational costs
- Partner with Engineering and Safety ML to productionize approaches and define data, logging, guardrails, monitoring, alerting, escalation, and rollback criteria
- Translate written policy and product requirements into modelable targets, labels, decision rules, reviewer workflows, and measurable outcomes
- Design staged rollouts, experiments, and observational analyses to measure real-world impact and downstream effects
- Support investigations and urgent escalations, conduct post-incident analyses, and develop durable detection or monitoring improvements
- Build reusable datasets, evaluation harnesses, monitoring tools, and documentation
- Communicate recommendations to technical and non-technical partners and mentor junior peers
- Track emerging abuse tactics and advances in adversarial ML, language models, synthetic data, and human-in-the-loop safety systems
Requirements:
- Ph.D. with 4+ years OR Master’s degree with 8+ years of relevant industry experience in Data Science, Applied Science, Economics, or a related quantitative role
- Applied experience in safety, enforcement engineering, fraud, or similar fast-paced, adversarial domains
- Expertise in SQL and Python for production-grade, reusable analytical code and data pipelines
- Strong background in statistical analysis, experiment design, causal modeling, and machine-learning techniques
- Practical knowledge of evaluating real-world decision systems, including sampling, label quality, class imbalance, precision/recall, calibration, thresholding, drift, and monitoring
- Ability to deconstruct ambiguous problems into scopable components and drive impactful decisions with cross-functional teams
- Exceptional communication skills for technical and non-technical stakeholders
- Role may involve exposure to sensitive content
- Participation in an incident-response on-call rotation, including occasional work outside normal hours
Benefits:
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
- Medical, dental, and vision insurance
- Equity in the form of restricted stock units
- Potential commission, depending on the position offered
- Interview recording opt-out option
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