Data and Model Ops Engineer

Visa • Atlanta, GA

112d • $104,600 - $147,900 • Hybrid

About The Position

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.

Requirements

• 2 or more years of work experience with a Bachelor's Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD).
• 3 or more years of work experience with a Bachelor's Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD).
• Up to 3 years of relevant experience with a PhD in Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent with analytics expertise in applying statistical solutions to business problems.
• Advanced proficiency in building and maintaining MLOps pipelines supporting the full model lifecycle, including development, validation, deployment, monitoring, and recalibration.
• Hands-on experience with deep learning frameworks and scalable machine learning model implementation in production environments.
• Strong background in data science, with demonstrated ability to optimize model performance and retrain models based on evaluation metrics.
• Expertise in developing high-performance ETL pipelines using Spark, Python, Hive, or Scala, with a focus on data standardization across diverse sources.

Responsibilities

• Build 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.
• 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 sources.
• Create data dictionaries, setup/monitor data validation alerts and execute periodic jobs like performance dashboards, predictive models scoring for client's deliverables.
• Define and build technical/data documentation and experience with code version control systems (for e.g., git).
• Ensure data accuracy, integrity and consistency.
• Strong 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 performance.
• Propose feasible solutions and effectively communicate strategy and risk mitigation approaches to leadership.

Benefits

• Medical
• Dental
• Vision
• 401 (k)
• FSA/HSA
• Life Insurance
• Paid Time Off
• Wellness Program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Credit Intermediation and Related Activities
• Education Level: Bachelor's degree