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Principal Data Scientist



Data Science
O'Fallon, IL, USA
Posted on Friday, May 24, 2024

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

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.

Join the industry’s most passionate, motivated & engaged global team - Our employees are encouraged to drive innovation every day in support of a more connected world – A World Beyond Cash.

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.

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 In the US, 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 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

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.

In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary based on location, experience and other qualifications for the role and may be eligible for an annual bonus or commissions depending on the role. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance), flexible spending account and health savings account, paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave), 10 annual paid sick days, 10 or more annual paid vacation days based on level, 5 personal days, 10 annual paid U.S. observed holidays, 401k with a best-in-class company match, deferred compensation for eligible roles, fitness reimbursement or on-site fitness facilities, eligibility for tuition reimbursement, gender-inclusive benefits and many more.