Job Title:

Senior Machine Learning Engineer-3

Overview:

Data Scientist – Data and Analytics

Career Level 7

Who is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is 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. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Overview
The Foundational AI team is looking for a data scientist with a particular interest in operationalizing and scaling ML/AI applications who is eager to take on the responsibility of contributing to a wide variety of data science projects. The person in this role will be join a team of leading edge data scientists who are not just building models, but are working to solve foundational business problems for the Company.

Role
In this role you will responsible for:

• Studying, transforming, and extending data science prototypes
• Searching cleaning, aggregating large data sets from Cloudera Hadoop, Azure, Splunk
• Application development and maintenance on Linux environments
• Performing statistical data analysis
• Iteratively training and retraining Machine Learning systems and models
• Extending existing ML frameworks and libraries
• Data visualization and story telling with Tableau, Jupyter, RShiny and/or d3s
• Graph analytics with Python, R or TigerGraph

About You
• Programming with Python and/or R languages
• Programming within ML Frameworks such as TensorFlow, PyTorch, scikit-learn, and/or Spark/ML
• Model deployment with containers such as Kubernetes and/or Docker
• Anomaly detection and model/data drift analysis affecting production ML models
• Building and maintaining ML production pipelines
• Solid verbal and written communication skills
• Bachelor of Science in Computer Science, Engineering, or Mathematics or similar field
• Experience with a Fortune 500 Company a plus
• Experience with graph databases a big plus.