Senior Data Scientist, Ads Integrity

Reddit · Remote - United StatesRemotosenior

En corto

▸Líder técnico en detección de fraude publicitario en Reddit, con enfoque en modelos escalables y pipelines de detección.
▸Trabajas con múltiples equipos (ML, ingeniería, operaciones, legal) para convertir hallazgos en sistemas de enfoque real.
▸Rol pionero en un área verde (sin precedentes en Reddit), con alta autonomía y capacidad de impacto directo.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

¿Qué piden?

✓Experiencia comprobada en detección de fraude en publicidad o entornos de anuncios digitales.
✓Habilidades avanzadas en análisis de datos a gran escala y redes de comportamiento.
✓Capacidad para diseñar y liderar el ciclo completo de detección: desde métricas hasta despliegue y monitoreo.
✓Experiencia en colaboración con equipos de ingeniería y machine learning para construir pipelines de detección.
✓Conocimiento en modelos estadísticos, ML y/o GenAI aplicados a problemas de integridad.
✓Capacidad para equilibrar riesgos de fraude, experiencia del usuario y objetivos comerciales.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

Machine LearningStatistical ModelingGenAIFeature EngineeringNear-Real-Time ScoringModel EvaluationA/B TestingData PipelinesObservabilityFraud Taxonomies

¿A quién escribirle en Reddit?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City & Chicago) our doors are open for you to come into the office as often as you'd like. Reddit is poised to innovate and grow like never before, and Safety is a critical accelerant of that growth. The Safety org is Reddit’s central Trust & Safety organization, protecting users from bad experiences by stopping harmful content, behaviors, and abuse across the platform. We are looking for a Senior Data Scientist to lead ads fraud detection and scaled enforcement within Safety. You will partner closely with Ads Product, Engineering, Machine Learning, Operations, Policy, Legal, and fellow Safety data scientists to identify emerging ads fraud, define rigorous measurement and evaluation standards, and turn investigations into durable signals, models, rules, and enforcement pipelines. This is a high-impact role with exceptional opportunity for ownership and growth: as an early leader in a greenfield space, you will help define the strategy, shape cross-functional roadmaps, build foundational capabilities, and expand your scope as Reddit’s ads integrity program matures. Responsibilities • Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks that make performance measurable and defensible. • Analyze large, complex datasets and networks of behavior to uncover emerging fraud patterns, size their impact, identify root causes, and translate findings into detection and enforcement requirements. • Design and develop scalable ads fraud detection and enforcement pipelines in partnership with Engineering and Machine Learning, including feature generation, rules and models, near-real-time scoring, actioning, review feedback loops, and observability. • Own the full detection lifecycle: backtesting, threshold calibration, offline and online evaluation, launch validation, experimentation, monitoring, drift detection, incident response, rollback, and retirement. • Build and maintain statistical, machine learning, and GenAI-enabled models or prototypes that improve fraud detection, risk identification, investigator efficiency, and enforcement quality. • Balance fraud loss, platform and advertiser risk, customer experience, false-positive costs, operational capacity, and business goals when recommending detection thresholds and enforcement strategies. • Partner across Ads and Safety to shape strategy and roadmaps, strengthen data foundations, close policy and enforcement gaps, and ensure solutions meet governance and compliance standards.<

No apliques sin prepararte

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