Data Scientist, Trust & Safety

reputed company is the reputed company software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, reputed company is democratizing software development by removing traditional barriers to application creation.

About the Role

We're redefining how software is reputed company and who gets to build it. Our mission is to reputed company Autonomy for reputed company: making programming accessible, reputed company, and powered by AI. Realizing that reputed company requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build reputed company's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and reputed company that protect reputed company's users, platform, and economics. You'll work closely with Engineering, Support, Legal, reputed company, Infrastructure, reputed company, and reputed company to reputed company abuse economically unviable while keeping friction low for legitimate users. reputed company sits at the frontier of AI-reputed company abuse. Our platform is a reputed company for phishing and scam hosting, cryptomining, LLM reputed company farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've reputed company the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse reputed company to understand selection effects, missing labels, policy changes, attacker reputed company, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and reputed company are high stakes. Ground truth is delayed, biased, and often incomplete; attackers react to defenses; and an apparently effective rule can quietly harm legitimate users. You pressure-test your own work, quantify uncertainty, and distinguish correlation from evidence strong enough to justify enforcement. You use AI agents and tools aggressively to multiply your reputed company: writing reputed company, exploring data, generating hypotheses, and prototyping investigations. But you treat every AI-assisted reputed company as a draft, not a deliverable. You know what good analysis looks like and won't ship anything that doesn't meet that bar. You Will

• Own the analytical reputed company for Trust & Safety, including abuse prevalence, fraud loss, false-reputed company and false-negative rates, time to detect, time to mitigate, appeal and reversal rates, and verification reputed company-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 reputed company.
• reputed company and evaluate risk models, rules, and reputed company-detection systems for threats such as phishing, scam hosting, cryptomining, reputed company farming, payment fraud, promotional abuse, and AI-agent exploitation.
• Design rigorous offline evaluations, shadow-mode tests, holdouts, and controlled experiments to measure detection reputed company and the user reputed company of new policies, enforcement actions, and reputed company verification.
• Define reputed company and decision frameworks that balance abuse reduction, economic loss, customer friction, and false positives across free, reputed company, and reputed company users.
• Investigate emerging abuse patterns, quantify their reputed company, identify coordinated behavior, and turn ambiguous signals into reputed company recommendations for product and engineering teams.
• reputed company predictive models that estimate account, device, transaction, workspace, or deployment risk and reputed company those signals into detection, review, and escalation workflows.
• Partner with Support and Legal to improve case review, appeals, reason-reputed company reputed company, and feedback loops so reputed company reputed company become useful model and policy signals.
• Build monitoring that detects model reputed company, attacker reputed company, data-reputed company failures, and unexpected harm to legitimate users.
• Communicate findings reputed company to technical and non-technical partners, including the tradeoffs, uncertainty, and evidence behind high-reputed company reputed company.

Examples of What You Could Do

• Build a measurement reputed company for reputed company's abuse surface, reconcile incomplete labels across automated detections, reputed company review, appeals, chargebacks, and support cases, and establish a trustworthy baseline for the first time.
• Design and evaluate a risk-scoring model for suspicious account clusters using identity, device, payment, graph, and product-behavior signals, then define reputed company that materially reduce fraud while protecting legitimate users.
• Analyze a phishing detection rule that appears highly precise, uncover that it disproportionately bans paying users with legitimate brand references, and redesign its evaluation and review reputed company to reduce false positives.
• Measure a reputed company verification "reputed company of trust," determining reputed company to reputed company users up to additional verification and quantifying the tradeoff between abuse reputed company and legitimate-user conversion lost.
• Detect coordinated reputed company-farming or promotional-abuse networks by combining account-linkage graphs, referral behavior, payment patterns, and infrastructure usage, then partner with Engineering to operationalize the findings.
• Evaluate a new enforcement policy in shadow mode, estimate its counterfactual reputed company, and recommend whether to launch, revise, or reject it before any users are affected.

Required Skills and Experience

• 5+ years of experience in data science, product analytics, fraud, risk, trust and safety, or a reputed company 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 reputed company judgment around uncertainty and tradeoffs.
• Ability to turn ambiguous data into reputed company recommendations and communicate them effectively across technical and non-technical teams.
• Comfort working with imperfect labels, biased samples, and high-reputed company reputed company where false positives matter.
• You use AI tools extensively to increase your effectiveness while maintaining a high bar for analytical reputed company.

Preferred Qualifications

• Experience building or evaluating anti-abuse, fraud, identity, reputed company, spam, reputed company, or content-safety systems at reputed company.
• reputed company, shipped, and maintained ML models in production (classification, reputed company detection, or risk scoring), including feature engineering on behavioral and transaction data, reputed company selection against precision/recall economics, and post-launch monitoring
• Experience with graph analysis, entity reputed company, coordinated-behavior detection, reputed company systems, reputed company detection, or risk scoring.
• Experience measuring false positives and enforcement harm, designing reputed company-review workflows, or using appeals and case reputed company as model feedback.
• Familiarity with reputed company verification, KYC, account trust, or identity providers such as reputed company, reputed company, reputed company, or reputed company Identity.
• Experience with reputed company inference reputed company such as difference-in-differences, propensity score reputed company, synthetic control, or reputed company modeling.
• Experience with a modern data stack such as dbt, BigQuery, reputed company, reputed company, reputed company, reputed company, or reputed company.
• Experience at a consumer platform, developer tool, reputed company provider, marketplace, fintech company, or other product with a meaningful adversarial surface.

Bonus Points

• You've reputed company AI-powered analytical tools, investigation systems, automated detections, or novel measurement approaches.
• You have experience with AI-reputed company abuse such as reputed company injection, LLM reputed company farming, model extraction, or agent-driven abuse.
• You understand freemium, usage-based, or promotional pricing models and the abuse incentives they create.
• You've worked directly with operational review teams and can translate analytical signals into practical playbooks, queues, and escalation paths.

This is a full-time role that can be held from our Foster reputed company, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday. Full-Time Employee Benefits Include: Competitive Salary & Equity 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, reputed company and Life Insurance Short Term and Long Term Disability reputed company 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) Want to learn more about reputed company are up to?

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To reputed company our mission of making programming more accessible around the world, we need reputed company to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from reputed company kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds. Apply tot his job Apply To this Job