Principal Data Scientist

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

Principal Data Scientist

All About Us
MasterCard is a technology company in the global payments business. We connect consumers, financial institutions, merchants, governments and businesses worldwide and enable them to use secure and convenient electronic forms of payment.
Overview
The Cyber and Intelligence Platform Data Science team is responsible for creating deep learning Artificial Intelligence (A.I.) and Machine Learning (M.L.) models. The models generated are production ready and created to back specific products in Mastercard’s authentication and authorization networks. The Data Science team is also responsible for developing automated processes for creating models covering all modeling steps, from data extraction up to delivery. In addition, the processes are must be designed to scale, to be repeatable, resilient, and industrialized.
You will be joining a team of Data Scientists working on innovative A.I. and M.L. fraud detection and anti-money laundering solutions. Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech, investment banking, biotech, healthcare, and insurance. We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge A.I. model evaluation and reporting processes.
Role
As a Principle Data Scientist, you will:
• Work closely with the business owners to understand business requirements, performance metrics regarding data quality and model performance of customer facing products
• Work with multiple disparate sources of data, storage systems, and build processes and pipelines to provide cohesive datasets for analysis and modeling
• Generate and maintain and optimize data pipelines for model building and model performance evaluation
• Overall responsibility for development, testing, and evaluation of modern machine learning and A.I. models for specific products
• Oversee implementation of models
• Evaluate production models based on business metrics to drive continuous improvement
All About You
Essential Skills:
• Data engineering experience
• Experience with SQL language and one or multiple of the following database technologies: PostgreSQL, Hadoop, Netezza, Spark, Oracle.
• Good knowledge of Linux / Bash environment
• Python and one of the following machine learning libraries
o Spark ML
o TensorFlow or related deep learning frameworks
o Scikit Learn
o XGBoost
• Good communication skills
• Highly skilled problem solver
• Exhibits a high degree of initiative
• At least an undergraduate degree in CS, or a STEM related field
• Prior experience in payment fraud detection modeling
Nice to have:
• Master’s or PhD in CS, Data Science, Machine Learning, AI or a related STEM field
• Experience in with data engineering and model building in PySpark using Spark ML on petabyte scale data
• Understands and implements methods to evaluate own work and others for bias, inaccuracy, and error
• Loves working with error-prone, messy, disparate, unstructured data
#AI1

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.