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Lead, AI Data Engineer

Lead, AI Data Engineer

MastercardO Fallon, MO, US
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Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. We're helping build a sustainable economy where everyone can prosper, supporting a wide range of digital payments choices and delivering secure, simple, smart, and accessible transactions.

The Cyber and Fraud Solutions Data Science team develops Artificial Intelligence products to help issuers, acquirers and merchants fight fraud. We are seeking a highly skilled and self-motivated AI Data Engineer to join our Data Science Team. In this role, you will design and build scalable data pipelines, robust feature engineering workflows, and create shared tools that empower data scientists across the organization.

Lead, AI Data Engineer

Lead role within Mastercard Services focused on acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.

  • Leading team in the creation of portfolio robust analytical solutions through effective use of Mastercard's global data assets and software platform
  • Independently maintain and organize data and tools for data transfer, mining, cleaning / processing, and validation
  • Design, build, and maintain data pipelines for structured and unstructured data used in AI / ML models
  • Develop and manage feature stores to support consistent feature computation across training and inference
  • Recommend ways to improve data quality and efficiency
  • Collaborate with ML Engineering and ML Ops teams in building DQ Drift Monitoring AI Systems
  • Contribute to the development of AI microservices for integrating data pipelines with model APIs
  • Collaborate with cross-functional teams and have opportunities to grow and develop as an AI Engineer

Technical Skills

  • Proficiency in Python and SQL
  • Experience with SQL databases : PostgreSQL, Oracle, Hadoop
  • Big Data Engineering : Spark, Kafka, Hive, Impala, Sqoop, AirFlow, NIFI
  • Linux / Bash environment, multiple scripting languages, and storage systems
  • Understanding machine learning workflows, model training, and inference pipelines
  • Building ML feature engineering workflows and familiarity with feature stores
  • Hands-on experience with cloud platforms
  • Experience building or supporting DQ drift monitoring systems for ML models
  • Understanding of data organization and security considerations
  • Business Skills

  • Strong communication, collaboration, and leadership ability
  • Subject matter expertise in payments, cards, and / or fraud, or the ability to learn quickly
  • Creativity, curiosity, and innovation
  • Ability to think outside the box and improve task accuracy and efficiency
  • Experience developing new products / services
  • Ability to integrate knowledge across disciplines to solve problems
  • Clear written and verbal communication of analyses and results to all levels
  • Excellent interpersonal skills, able to work remotely or in-person
  • Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment 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 come with inherent risk. 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.
  • Note : This description reflects responsibilities and qualifications for a Lead AI Data Engineer position and does not include all possible duties. Compensation and benefits are aligned with Mastercard's policies and location.

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    Lead Data Engineer • O Fallon, MO, US

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