To ensure that Visa’s payment technology is truly available to everyone, everywhere requires the success of our key bank or merchant partners and internal business units. The Intelligence and Data Solutions team supports these partners by using our extraordinarily rich data set that spans more than 3 billion cards globally and captures more than 100 billion transactions in a single year. Our focus lies on building creative solutions that have an immediate impact on the business of our highly analytical partners. We work in complementary teams comprising members from Data Science and Data Engineer at Visa. To support our rapidly growing group we are looking for Data and MLOps Engineer who are equally passionate about the opportunity to use Visa’s rich data to tackle meaningful business problems. Essential FunctionsBuild MLOps pipelines to support model development, model production, model validation, model performance monitoring, model recalibration, continuous integration, continuous delivery of AI/ML models.New model development and existing model re-training, performance evaluation and score optimization. Preferable to have data science knowledge and experience in designing, developing and implementing Deep Learning methodologies, and newer ML model implementations at scale.Build and maintain high performing ETL processes including data quality and testing aligned across technology, internal reporting and other functional teams.Build ETL pipelines in Spark, Python, HIVE or Scala that process transaction and account level data and standardize data fields across various data sourcesExposure to model management and governance practices. Ability to take decisions around model drift to monitor and refine models continuously.Create data dictionaries, setup/monitor data validation alerts and execute periodic jobs like performance dashboards, predictive models scoring for client’s deliverablesDefine and build technical/data documentation and experience with code version control systems (for e.g., git). Ensure data accuracy, integrity and consistencyStrong understanding of development and implementation aspects of ML/AI, especially on billion-scale datasets. Ability to take small scale developed models as input and implement with requisite configuration and customization, while maintaining model performanceShould have strong problem-solving capabilities and ability to quickly propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager. 
