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

Data / ML Engineer-4

Mastercard Overview

Mastercard is the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee can be a part of something bigger and change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities.
Join a fast-growing team
As a Data / ML Engineer in the Data Engineering & Analytics team, you will develop data & analytics 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, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data. You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc.

Your Role
• Drive the evolution of Data & Services products/platforms with an impact-focused on data science and engineering.
• Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
• Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
• Provide support for deployed data applications and analytical models by being a trusted advisor to Data Scientists and other data consumers by identifying data problems and guiding issue resolution with partner Data Engineers and source data providers.
• Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
• Discover, ingest, and incorporate new sources of real-time, streaming, batch, and API-based data into our platform to enhance the insights we get from running tests and expand the ways and properties on which we can test Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
• Maintain awareness of relevant technical and product trends through self-learning/study, training classes and job shadowing.
• Participate in the development of data and analytic infrastructure for product development
Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations
• Partner with roles across the organization including consultants, engineering, and sales to determine the highest priority problems to solve
• Evaluate trade-offs between many possible analytics solutions to a problem, taking into account usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision
Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients, and other stakeholders
• Evangelize releases to users, incorporating feedback, and tracking usage to inform future development
Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
• Work with small, cross-functional teams to define the vision, establish team culture and processes
Consistently focus on key drivers of organization value and prioritize operational activities accordingly
• Escalate technical errors or bugs detected in project work
• Maintain awareness of relevant technical and product trends through self-learning/study, training classes, and job shadowing.
• Support the building of scaled machine learning production systems by designing pipelines and engineering infrastructure.
Ideal Candidate Qualifications:
• Experience and exposure to Python/Scala, Spark(tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms
• Experience with data pipeline and workflow management tools: NIFI, Airflow.
• Comfortable in developing shell scripts for automation
• Proficient in standard software development, such as version control, testing, and deployment
• Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering
• Curiosity, creativity, and excitement for technology and innovation
• Demonstrated quantitative and problem-solving abilities
• Motivation, flexibility, self-direction, and desire to thrive on small project teams
• Good communication skills - both verbal and written – and strong relationship, collaboration skills, and organizational skills
• At least a Bachelors degree in Computer Architecture, Computer Science, Electrical Engineering or equivalent experience. Postgraduate degree is an advantage
The following skills will be considered as a plus
• Experience with visualization tools like tableau, looker
• Hands-on experience with cloud computing and big data frameworks e.g. GCP, AWS, Azure, Flink, Elasticsearch, and Beam
• Knowledge in MLOps frameworks such as TensorFlow Extended, Kubeflow, or MLFlow
• Experience participating in complex engineering projects in an Agile setting e.g. Scrum

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.