Senior Data Scientist – Data, AI

Globo

Cientista de Dados Sênior criando modelos antifraude para a Globo, empresa de mídia e produtos digitais. Desenvolvendo scoring em tempo real, monitoramento de modelos e soluções de ML orientadas a risco.

Posted 8/18/2026full-timePorto Alegre • 🇧🇷 BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and productionizing ML models for fraud detection, with proficiency in Python, SQL, and MLOps practices. Capable of collaborating across teams to balance fraud prevention with user experience while mentoring junior team members.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProficiencySQL ProficiencyMLOps ExperienceFraud Detection Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningClassificationAnomaly DetectionFeature EngineeringModel MonitoringData AnalysisCloud ComputingData HandlingModel ExplainabilityGraph-Based Modeling

Soft Skills

Strong CommunicationTeam CollaborationMentoring

Tools & Technologies

Scikit-LearnXGBoostLightGBMTensorFlowPyTorchGCPVertex PipelinesCI/CDGitGenerative AI

Certifications & Qualifications

Bachelor's Degree in Data ScienceStatisticsMathematicsComputer Science

Industry Keywords

Fraud PreventionRisk ManagementProduction Anomaly DetectionImbalanced ClassesPrecision/RecallPR-AUCCost-Aware Confusion MatrixLow-Latency Online Prediction APIsContinuous TrainingModel Drift Detection

Tech Stack

Tools & technologies

Google Cloud PlatformPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Build, train and productionize ML models for fraud detection and prevention, including classification and anomaly detection
Develop and maintain real-time or near-real-time scoring pipelines for risk decisions
Monitor model performance and drift in production, with continuous retraining
Perform feature engineering on transactional and behavioral data
Collaborate with risk, product and engineering teams to balance fraud prevention and legitimate user experience
Explore generative AI as a support tool for analysis, prototyping and documentation
Act as a technical reference, supporting architecture decisions and mentoring more junior team members
Work with ML engineers, data engineers and product owners on data-driven solutions

Requirements

What you’ll need

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science or a related field
Solid experience as a Data Scientist, working autonomously on end-to-end ML projects from conception to production
Proficiency in Python and SQL for data analysis and modeling
Experience with classification and/or anomaly detection, including handling imbalanced classes
Familiarity with precision/recall, PR-AUC and cost-aware confusion matrix
Knowledge of Scikit-Learn and XGBoost/LightGBM; TensorFlow or PyTorch is a plus
Familiarity with MLOps, model monitoring, drift detection and continuous training
Experience with cloud computing, preferably GCP
Experience handling large volumes of data
Knowledge of software development best practices, CI/CD and Git
Strong communication skills and ability to collaborate in a team
Prior experience with anti-fraud, risk or production anomaly detection is a plus
Graph-based modeling for network fraud detection is a plus
Experience with low-latency online prediction APIs is a plus
Knowledge of model explainability, including SHAP and feature importance, is a plus
Familiarity with generative AI/LLMs is a plus
Advanced experience with MLOps on GCP, Vertex Pipelines and Model Monitoring is a plus
Intermediate/advanced English is a plus

Benefits

Comp & perks

Inclusive, welcoming and supportive environment
100% remote hiring process
Opportunity to mentor junior colleagues and act as a technical reference