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# Senior Director, Data Scientist - Global Payment Network

- **Company:** Capital One Financial Corporation
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $269,600.0 - $307,700.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Data Systems, Relational Databases, Python (Programming Language), Machine Learning, Open Source Technology, Cloud Platform System, Apache Spark, Information Technology, Data Analytics
- **Published:** October 2, 2026
- **Apply:** https://dejobs.org/x/x/5BEC93DA9E7F4FC5BF9B22821F1AE89E/job/

## About the Role

* A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
 * Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
 * Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
 * Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms., * Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date :
 * A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 11 years of experience performing data analytics
 * A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 9 years of experience performing data analytics
 * A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
 * At least 6 years of experience leveraging open source programming languages for large scale data analysis
 * At least 6 years of experience working with machine learning
 * At least 6 years of experience utilizing relational databases, * Extensive multi-project experience leading data science solutions within payments, financial services, or fintech sectors.
 * At least 1 year of experience working with AWS
 * At least 4 years of experience managing people
 * At least 6 years of experience in Python, Scala, or R for large scale data analysis
 * At least 7 years of experience with machine learning

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

## Description

The Global Payment Network Data Solutions and Modeling team builds the machine learning and AI agents to drive foundational, scalable intelligence capabilities that power smarter business decisions and unlock new value across the payments ecosystem. We create models and AI tools to support fraud/risk, merchant acceptance, merchant intelligence and monitoring., * Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love

 * Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
 * Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
 * Flex your interpersonal skills to translate the complexity of your work into tangible business goals


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