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MasterCard ML and Data Platform Lead Engineer in San Francisco, California

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 (https://www.mastercard.us/en-us/vision/who-we-are/diversity-inclusion.html) 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.

Job Title

ML and Data Platform Lead Engineer

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 to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities.

“AI at scale” enables data scientists to deploy Deep Learning workloads on their current DW Hadoop Distributed Spark Environment using popular DL frameworks - TensorFlow, Keras without investing extra money and effort on new GPU clusters.

“AI at scale” leverages MLOps Automation to enable rapid development, experimentation, and automated triggering of AI/ML pipelines. This greatly reduces Cycle Time for deploying new models into Production.

“AI at scale” also aligns to Mastercard's strategy to increase revenue from Data and Services, a full on-prem solution (current state) may not be ideal to future-proof our organization. Hence, though the cloud base AI at Scale solution, we aim to prove the technical feasibility of using such a solution for couple of use cases, address privacy concerns, and in the long run, move towards a hybrid (on-prem + cloud) technical infrastructure that allows us to improve our capabilities and reduce costs.

As a ML and Data Platform Lead Engineer, you will have the opportunity to build high performance data and AI pipelines to load into Mastercard Data Warehouse and enable “AI at scale” capabilities.

Our Data Warehouse provides analytical capabilities to number of business users who help different customers provide answer to their business problems through data. You will play a vital role within a rapidly growing organization, while working closely with experienced and driven engineers to solve challenging problems.

Your Role

• Lead the design the next implementation of Mastercard secure, global data and AI platform architecture and “AI at Scale”

• Part of a team building data platform infrastructure and tools for exciting new technologies that will shape the future

• 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

• Prototype new algorithms, experiment, evaluate and deliver actionable insights.

• Collaborate with other data engineering and data science teams to improve the data engineering ecosystem and talent within Mastercard.

• Creatively solve problems when facing constraints, whether it is the number of developers, quality or quantity of data, AI lifecycle, compute power, storage capacity or just time.

All About You

• At least Master's degree in Computer Science, Data Science and Big Data Analytics | Statistics, Computer Engineering or Technology related field or equivalent work experience

• Experience in Data Warehouse related projects in product or service-based organization

• Have hands-on experience in building distributed systems, including real-time streaming and batch data processing

• Proficient in multiple programming languages relevant for such systems (e.g., Java, Python)

• Experience working with ML frameworks like TensorFlow, PyTorch, Scikit-learn, Spark ML, Torch, or Keras

• Experience end-to-end model building using MF, FM, DFM, RL, SGD, SVM, RNN, or DNN and deployment experience

• Professional experience working in a product-driven environment for recommendation systems, search, natural language processing, or similar

• Experience working with big data & distributed systems and computing tools like S3, Hive, MapReduce, and Spark

• Experience with cloud computing platform like AWS, GCP and Azure

• Expertise in Data Engineering and implementing multiple end-to-end DW projects in Big Data environment

• Experience in building and deploying production level data driven applications and data processing workflows/pipelines

• Experience of working in Agile teams

• Strong analytical skills required for writing and performance tuning complex SQL queries, debugging production issues, providing root cause, and implementing mitigation plan

• Strong communication skills - both verbal and written – and strong relationship, collaboration skills and organizational skills

• Ability to be high-energy, detail-oriented, proactive, and able to function under pressure in an independent environment along with a high degree of initiative and self-motivation to drive results

• Ability to quickly learn and implement new technologies, and perform POC to explore best solution for the problem statement

• Flexibility to work as a member of a matrix based diverse and geographically distributed project teams

Due to COVID-19, most of our employees are working from home. We’ve implemented a virtual hiring process and continue to interview candidates by phone or video and are onboarding new hires remotely. We value the safety of each member of our community because we know we’re all in this together.

Mastercard is an inclusive Equal Employment Opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.​

If you require accommodations or assistance to complete the online application process, please contact reasonable.accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility

Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and therefore, it is expected that the successful candidate for this position 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.

Requisition ID: R-139599

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