Capital One Manager Data Scientist - Card Risk 

United States, Virginia, Arlington 

646384217

Center 1 (19052), United States of America, McLean, Virginia Manager, Data Scientist - Card Risk

In this role, you will:

• Build end-to-end innovative data science solutions to solve business pain points and accelerate stakeholders and end users adoptions of the solutions

• Partner with a cross-functional team of data analysts, risk professionals, software engineers, and product managers to manage the risk and uncertainty inherent in statistical models in order to lead Capital One to the best decisions, not just avoid the worst ones

• Leverage a broad stack of technologies — Python, Conda, Flask, Dash, Hugging Face, LangChain, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data

• Build machine learning and NLP models through all phases of development, from design through training, evaluation, validation, and implementation.

• Productionize highly scalable data pipelines for faster feature changes and updates, and implementing data validation framework and quality tests

• Investigate new technology to advance data management, model development and deployment and drive change in enterprise ML products

• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

• 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.

• ​​Collaboration and Communication. You’re capable of effectively articulating data insights and analytics strategies to a diverse audience, including risk managers, engineers, product managers and leadership.

• Statistically-minded. You’ve built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

• A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

• Currently has, or is in the process of obtaining a Bachelor’s Degree plus 6 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 4 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date

• At least 2 years’ experience in open source programming languages for large scale data analysis

• At least 2 years’ experience with machine learning

• At least 2 years’ experience with relational databases

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics

• At least 1 year of experience working with AWS

• At least 4 years’ experience in Python, Scala, or R for large scale data analysis

• At least 4 years’ experience with machine learning

• At least 4 years’ experience with SQL

. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.