Lead Data Scientist

Full time

Employment Information

Job levelSenior level

Salary$118 000 - $183 000

IndustryIT Services and IT Consulting

Experience4+ years

LocationO'Fallon, MO, United States

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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

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.

As a Lead 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
Oversee implementation of models
Evaluate production models based on business metrics to drive continuous improvement

Essential Skills:

Data engineering experience
Experience with SQL language and one or multiple of the following database technologies: PostgreSQL, Hadoop, Netezza, Spark.
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:

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 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

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.