Machine Learning Engineer II

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Machine Learning Engineer II

Overview

As a Data Engineer on the Data Science & AI team, you will develop data products and solutions built on vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge machine learning techniques, including deep learning, and intuitive workflows that enable our users to derive insights from big data, which in turn drive their businesses, all while maintaining a keen eye for data privacy. You will have the opportunity to create high-performance analytical solutions based on datasets containing billions of transactions, as well as front-end visualizations to unlock the value of big data.
You will also have the opportunity to develop innovative, data-driven analytical solutions, identify opportunities to support business and client needs quantitatively, and facilitate informed recommendations/decisions through activities such as AI-driven engineering solutions, automated data pipelines, and executing jobs in big data clusters using various execution engines like Spark, Hive, Impala, and others.

Role
In this role, you will:
• Build, deploy, and maintain production-level, data-driven applications and data processing workflows or pipelines.
• Work with testing frameworks and follow test-driven development (TDD) practices.
• Understand product requirements, engage with team members and customers to define solutions, and estimate the scope of work required.
• Utilize quantitative and qualitative problem-solving abilities to quickly learn and implement new technologies, and perform POCs to explore the best solutions for the problem statement.
• Work as a member of a matrix-based, diverse, and geographically distributed project team.

Qualifications
• You possess a degree or master's in Computer Science, Applied Mathematics, Engineering, or a related field.
• You have intermediate experience as a Machine Learning Engineer, Software Engineer, Data Engineer, and/or in a Data Solutions role.
• You have experience deploying machine learning models.
• High proficiency in Python and SQL.
• Experience with cloud-native big data frameworks (e.g., Hadoop, Yarn, Spark, Impala, Hive, NiFi, Airflow).
• Experience deploying solutions in cloud environments (e.g., Cloudera, Databricks, AWS) and using services (e.g., Tableau, Power BI, Databricks SQL dashboards).
• Experience working with engineering best practices (e.g., Git, Jira, DevOps).
• Solid understanding of data modeling, data monitoring, data dashboarding, database design, and data warehousing concepts.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.