Our team within Mastercard:
The Data & Services team is a key differentiator for Mastercard, providing the cutting-edge services that are used by some of the world's largest organizations to make multi-million dollar decisions and grow their businesses. Focused on thinking big and scaling fast around the globe, this agile team is responsible for end-to-end solutions for a diverse global customer base. Centered on data-driven technologies and innovation, these services include payments-focused consulting, loyalty and marketing programs, business Test & Learn experimentation, and data-driven information and risk management services.

The New Product Engineering team within Data and Services is engineering the transformation of new ideas into software solutions to test in the market, and then growing and scaling products to meet long-term demand and needs. We achieve this with a "move fast, learn fast" mindset, relentless focus on customer excellence, and a culture of collaboration and empowerment. Our solutions are instrumental in positioning Mastercard as a data & services market leader.

Role and Summary

Data Scientist

The Data Scientist in Data & Services New Product Engineering team is responsible for creating data & analytics solutions including deep learning Artificial Intelligence (A.I.) and Machine Learning (M.L.) models that sit atop large datasets of business and finance operations gathered by mid to large companies. The Data Scientist is responsible for developing full life cycle modeling processes of data analysis, feature engineering, model training, testing, serving and monitoring.

As a 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 building 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
Develop, test, and evaluate modern machine learning and A.I. models
Develop highly scalable and efficient data pipelines to automate data ingestion and end-to-end data movement
Oversee implementation of models
Evaluate production models based on business metrics to drive continuous improvement

Essential Skills:

Data engineering and data science experience
Experience with SQL language and one or multiple of the following database technologies: PostgreSQL, Hadoop, Spark.
Familiar with data pipeline technologies and best practices with industry leading platforms such as Apache NiFi, Airflow or equivalent
Good knowledge of Linux / Bash environment
Python and one of the following machine learning libraries
Spark ML
TensorFlow
Scikit Learn
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.

Nice to have:

Bachelor's or Master's in CS, Data Science, ML/AI, or a related STEM field
Understands and implements methods to evaluate own work and others for bias, inaccuracy, and error
Loves working with error-prone, messy, disparate, unstructured data
Experience in working with Cloud (e.g., Azure, AWS)
Experience participating in complex engineering projects in an Agile setting e.g. Scrum

Mastercard is an equal opportunity employer that values diversity and inclusion. Applicants will be considered and treated without regard to gender, gender identity, race, color, ethnicity, national origin, religion, sexual orientation, veteran or disabled status, or any other characteristic protected by applicable law.

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.