Director of Data Scientist, Mastercard

• Extensive data science experience and significant leadership roles
• Demonstrated full lifecycle model development, deployment and evaluation for complex problems
• Experience with SQL language and the following technologies: PySpark, Hadoop, Databricks
• Good knowledge of Linux / Bash environment
• Python
• XGBoost
• Good communication skills
• Highly skilled problem solver
• Exhibits a high degree of initiative
• At least an undergraduate degree in CS, or a STEM related field
• Prior experience in payment fraud detection modeling

Desirable

• The Security Solutions Data Science team is responsible for creating Artificial Intelligence (AI) and Machine Learning (ML) models backing its flagship product
• The models generated are production ready and created to back specific products in Mastercard’s authentication and authorization networks
• The Data Science team is also responsible for developing automated processes for creating models covering all modeling steps, from data extraction up to delivery
• In addition, the processes must be designed to scale, to be repeatable, resilient, and industrialized
• You will be joining a team of Data Scientists and engineers working on innovative AI and ML fraud detection
• Be a senior practitioner and lead a team of data scientists delivering production quality fraud models that run in real time to screen transaction networks
• Work closely with the business owners to understand business requirements, performance metrics regarding data quality and model performance of customer facing products
• Work with multiple disparate sources of data, storage systems, and build processes and pipelines to provide cohesive datasets for analysis and modeling
• Generate and maintain and optimize data pipelines for model building and model performance evaluation
• Set the roadmap and identify methods and approaches that enhances the performance of existing fraud detection models
• Overall responsibility for development, testing, and evaluation of modern machine learning and AI models for specific products
• Oversee implementation of models
• Evaluate production models based on business metrics to drive continuous improvement