Senior Data Scientist – Fraud Prevention

• Lead end-to-end Data Science projects, from defining the problem with Product and Operations to delivering solutions to production
• Track business impact and continuously improve solutions
• Design, implement, and maintain production Machine Learning pipelines, both batch and online
• Ensure reliability, scalability, and maintainability in high-volume, low-latency environments
• Manage the model lifecycle: experimentation, validation, deployment, monitoring, and iteration
• Define metrics and monitoring routines for data drift and concept drift
• Develop and enhance batch and real-time inference systems
• Work with architectural trade-offs involving parallelization, concurrency, and low latency
• Optimize latency, throughput, and computational resource usage
• Establish and improve MLOps practices, including infrastructure, deployment, observability, version control, automation, and continuous monitoring
• Partner with Engineering Tech Leaders and Product Managers to design solutions and enable production deliveries
• Stay up to date with Data Science best practices and AI-assisted development tools

• Strong command of classic Machine Learning algorithms for classification and regression, including XGBoost, LightGBM, and Random Forest
• Experience productionizing and maintaining live and batch Machine Learning models
• Experience with live models delivered through APIs, high concurrency, and low latency
• Experience managing and monitoring models in production
• Proficiency with frameworks such as MLflow
• Proficiency in SQL, Python, and Spark for analyzing large datasets
• Knowledge of statistical inference and practical experience applying A/B tests
• Familiarity with structured development and code version control using Git
• Ability to communicate technical results and translate statistical metrics into business impact
• Bachelor’s degree or equivalent practical experience in Computer Science, Engineering, Statistics, Mathematics, Physics, or a related field
• Preferred qualifications: experience with Databricks, fintech companies, the payments market or financial institutions, fraud prevention, financial fraud metrics, Kafka, Kinesis, Graph Data Science, graph databases, and AWS

• Medical and dental insurance with no copay
• Life insurance
• Prescription medication assistance
• Fitness benefit
• Four free therapy or nutritionist sessions per month through Zenklub
• Quick massage at headquarters
• Flexible food allowance on a Visa card
• Complimentary food at headquarters
• Childcare assistance
• Parental support program
• Extended maternity and paternity leave
• In-house training platform
• Education assistance covering 70% of tuition for undergraduate degrees and language courses, as well as courses and books
• Home office allowance
• Work equipment
• Home office furniture allowance
• Partnership with WOBA for coworking access throughout Brazil
• Birthday-month day off
• Happy hour allowance
• Referral bonus for new hires
• Annual performance-based bonus
• Stock option plan
• No dress code