Principal Data Scientist
O'Fallon, Missouri (Main Campus)
Mastercard
Wir verbinden und fördern eine integrative, digitale Wirtschaft, von der Menschen, Unternehmen und Regierungen weltweit profitieren, indem wir Transaktionen sicher, einfach und zugänglich machen.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 ScientistAll About UsMasterCard 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.
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 dataIn 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Banking Data pipelines Data quality Deep Learning Engineering Hadoop Linux Machine Learning Oracle PhD Pipelines PostgreSQL PySpark Python Scikit-learn Security Spark SQL STEM TensorFlow Testing Unstructured data XGBoost
Perks/benefits: 401(k) matching Career development Competitive pay Fitness / gym Flex hours Flexible spending account Flex vacation Health care Insurance Medical leave Salary bonus Team events
More jobs like this
Explore more AI, ML, Data Science career opportunities
Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
- Open Data Manager jobs
- Open Power BI Developer jobs
- Open Principal Data Engineer jobs
- Open Marketing Data Analyst jobs
- Open Data Science Manager jobs
- Open Lead Data Analyst jobs
- Open MLOps Engineer jobs
- Open Senior Business Intelligence Analyst jobs
- Open Business Data Analyst jobs
- Open Data Analytics Engineer jobs
- Open Data Scientist II jobs
- Open Business Intelligence Developer jobs
- Open Product Data Analyst jobs
- Open Sr Data Engineer jobs
- Open Junior Data Scientist jobs
- Open Data Analyst Intern jobs
- Open Senior Data Architect jobs
- Open Sr. Data Scientist jobs
- Open Principal Data Scientist jobs
- Open Research Scientist jobs
- Open Big Data Engineer jobs
- Open Data Quality Analyst jobs
- Open Azure Data Engineer jobs
- Open Manager, Data Engineering jobs
- Open ML Engineer jobs
- Open GCP-related jobs
- Open Data quality-related jobs
- Open Java-related jobs
- Open ML models-related jobs
- Open Business Intelligence-related jobs
- Open Data management-related jobs
- Open Privacy-related jobs
- Open Data visualization-related jobs
- Open PhD-related jobs
- Open Deep Learning-related jobs
- Open NLP-related jobs
- Open Finance-related jobs
- Open PyTorch-related jobs
- Open TensorFlow-related jobs
- Open APIs-related jobs
- Open LLMs-related jobs
- Open Consulting-related jobs
- Open Generative AI-related jobs
- Open CI/CD-related jobs
- Open Snowflake-related jobs
- Open Kubernetes-related jobs
- Open Hadoop-related jobs
- Open Data governance-related jobs
- Open Databricks-related jobs
- Open Data warehouse-related jobs