Data and Model Ops Engineer

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

​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 Functions

• 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. 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 sources
• Exposure 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 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
• Should 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.

Qualifications

Basic Qualifications

• 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications

• 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.

Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer.  Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.  Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 104,600.00 to 147,900.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.