Data Scientist, Trust & Safety

Replit

Data Scientist in Engineering at Replit, focusing on Trust & Safety and Anti-Abuse program development against various online threats.

Posted 7/21/2026full-timeFoster City • California • 🇺🇸 United StatesMid-LevelSenior💰 $210,000 - $310,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and evaluating predictive models, risk assessments, and anomaly-detection systems while effectively communicating complex findings to both technical and non-technical stakeholders. Proficient in SQL and Python for building reliable data models and pipelines, with a strong focus on trust and safety analytics.

Highest-signal resume keywords

SQLPythonPredictive Model DevelopmentRisk AssessmentData Analysis

ATS Keywords

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Hard Skills

Data ScienceProduct AnalyticsFraud DetectionRisk ModelingAnomaly DetectionData ModelingStatistical AnalysisExperimental DesignDecision SystemsBehavioral Data Analysis

Soft Skills

Effective CommunicationJudgment Around UncertaintyProblem-SolvingCollaboration

Tools & Technologies

AI ToolsData PipelinesMonitoring SystemsDBT Models

Industry Keywords

Trust and SafetyFraud LossFalse PositivesCustomer FrictionBehavioral DatasetsEmerging Abuse PatternsModel Drift

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Own the analytical foundation for Trust & Safety, including abuse prevalence, fraud loss, false-positive and false-negative rates, time to detect, time to mitigate, appeal and reversal rates, and verification step-up conversion.
Build reliable datasets and dbt models that connect product events, account and identity signals, payment activity, infrastructure usage, content classifications, enforcement actions, appeals, and support outcomes.
Develop and evaluate risk models, rules, and anomaly-detection systems for threats such as phishing, scam hosting, cryptomining, token farming, payment fraud, promotional abuse, and AI-agent exploitation.
Design rigorous offline evaluations, shadow-mode tests, holdouts, and controlled experiments to measure detection quality and the user impact of new policies, enforcement actions, and progressive verification.
Define thresholds and decision frameworks that balance abuse reduction, economic loss, customer friction, and false positives across free, paid, and enterprise users.
Investigate emerging abuse patterns, quantify their impact, identify coordinated behavior, and turn ambiguous signals into clear recommendations for product and engineering teams.
Develop predictive models that estimate account, device, transaction, workspace, or deployment risk and embed those signals into detection, review, and escalation workflows.
Partner with Support and Legal to improve case review, appeals, reason-code quality, and feedback loops so human decisions become useful model and policy signals.
Build monitoring that detects model drift, attacker adaptation, data-quality failures, and unexpected harm to legitimate users.
Communicate findings clearly to technical and non-technical partners, including the tradeoffs, uncertainty, and evidence behind high-impact decisions.

Requirements

What you’ll need

5+ years of experience in data science, product analytics, fraud, risk, trust and safety, or a related field.
Strong SQL and Python skills, with experience working with large behavioral datasets and building reliable data models or pipelines.
Experience developing and evaluating predictive models, experiments, or decision systems, with sound judgment around uncertainty and tradeoffs.
Ability to turn ambiguous data into clear recommendations and communicate them effectively across technical and non-technical teams.
Comfort working with imperfect labels, biased samples, and high-impact decisions where false positives matter.
You use AI tools extensively to increase your effectiveness while maintaining a high bar for analytical quality.

Benefits

Comp & perks

Competitive Salary & Equity
401(k) Program with a 4% match (*US Only*)
Health, Dental, Vision and Life Insurance
Short Term and Long Term Disability
Paid Parental, Medical, Caregiver Leave
Flexible Time Off (FTO) + Holidays
Commuter Benefits (*In-Office Only*)
Monthly Wellness Stipend
Autonomous Work Environment
In Office Set-Up Reimbursement (*In-Office Only*)
Quarterly Team Gatherings
In Office Amenities (*In-Office Only*)