Our Purpose

We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.

Title and Summary

Machine Learning Engineer II

Overview:
As Machine Learning Engineer II of the Data Science & Engineering team, you will develop analytical products and solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms built on data sets measured in the billions of transactions that allow our users to derive insights from big data that in turn drive their businesses with a keen eye for data privacy and governance.

Role:
- Participate in development of portfolio robust ML solutions through effective use of Mastercard’s global data assets and software platform
- Build, productionize and maintain AI/ML application and data processing workflows or pipelines
- Liaise with internal stakeholders (e.g., MA TECH, Data Strategy Management, AI governance) to identify and elaborate on opportunities as they relate to analytical solution development, feasibility, and other technical offerings
- Identify and recommend opportunities to standardize and automate efforts to ensure quality and enable scaling of ML products
- Meet project deadlines for accountable deliverables and anticipates delays or foreseeable barriers to progress and escalates issues when necessary
- Conduct due diligence quality assurance testing for prototypes and tools in stage and resolves reoccurring complex issues and bugs
- Develops presentations and ensures thorough technical documentation

All about you:
- Experience in Big Data Technologies: Proficiency in big data frameworks and tools such as Hadoop, Spark, Hive
- Technical Proficiency: Strong programming skills in languages such as Python and SQL. Experience with data visualization tools (e.g., Tableau, Power BI) and understanding of cloud computing services (AWS, Azure, GCP) related to data processing and storage is a plus.
- Experience with testing frameworks and test-driven development (TDD) practices
- Advanced Analytical Skills: Applied knowledge and hands on experience in machine learning algorithms and deep learning frameworks. Familiarity with AI and machine learning platforms such as TensorFlow, PyTorch, or similar.
- Problem-Solving Skills: Strong analytical and critical thinking abilities to solve complex problems, along with the creativity to find innovative solutions.
- Communication and Collaboration: Excellent verbal and written communication skills, with the ability to explain complex analytical concepts to non-technical stakeholders. Experience in working cross-functionally with departments and flexibility to work as a member of a matrix based diverse and geographically distributed project teams.
- Project Management Skills: Proficiency in managing multiple priorities with a focus on delivering results within tight deadlines.
- Innovation and Continuous Learning: A mindset geared towards innovation, staying abreast of industry trends, emerging technologies in big data and analytics, and continuously seeking opportunities for personal and professional growth

#AI

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.