Senior Data Scientist, Safety Enforcement

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of one or more specified enforcement challenges, encompassing problem framing, signal discovery, labeling, taxonomy, model or rule development, thresholding, rollout, monitoring, and iteration.

• Examine large-scale behavioral, content, account, and network data to uncover adversarial patterns, identify emerging threats, and highlight mitigation gaps.

• Create models, classifiers, scoring systems, rules, and analytical prototypes utilizing statistical, machine-learning, or GenAI methods.

• Establish evaluation frameworks that address precision, recall, calibration, coverage, robustness, fairness, user friction, reviewer capacity, and operational costs.

• Collaborate with Engineering and Safety ML to implement production-ready solutions and define data, logging, guardrails, monitoring, alerting, escalation, and rollback criteria.

• Convert written policy and product requirements into modelable targets, labels, decision rules, reviewer workflows, and measurable outcomes.

• Design staged rollouts, experiments, and observational analyses to assess real-world impact and downstream effects.

• Assist in investigations and urgent escalations, perform post-incident analyses, and propose sustainable detection or monitoring enhancements.

• Develop reusable datasets, evaluation harnesses, monitoring tools, and documentation.

• Present recommendations to both technical and non-technical stakeholders and mentor junior colleagues.

• Monitor emerging abuse tactics and developments in adversarial ML, language models, synthetic data, and human-in-the-loop safety systems.

⛳️ Requirements

• Ph.D. with 4+ years of experience OR Master’s degree with 8+ years of relevant industry experience in Data Science, Applied Science, Economics, or a related quantitative field.

• Proven experience in safety, enforcement engineering, fraud, or other similar fast-paced, adversarial environments.

• Proficiency in SQL and Python for developing production-grade, reusable analytical code and data pipelines.

• Strong foundation in statistical analysis, experimental design, causal modeling, and machine-learning methodologies.

• Practical understanding of evaluating real-world decision systems, including aspects like sampling, label quality, class imbalance, precision/recall, calibration, thresholding, drift, and monitoring.

• Ability to break down ambiguous problems into scoping components and facilitate impactful decisions with cross-functional teams.

• Outstanding communication skills for engaging with both technical and non-technical stakeholders.

• This role may require exposure to sensitive content.

• Participation in an incident-response on-call rotation, which may occasionally involve work outside of regular hours.

🏝️ Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs.

• 401k with Employer Match.

• Global Benefit programs tailored to your lifestyle, including workspace, professional development, and 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, based on the position offered.

• Interview recording opt-out option.