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The Consumer Protection Data Science team builds the machine learning models that help our customers get access to their money when they need it while also protecting them from fraudsters. We do this with cutting edge machine learning models while also pushing our creativity to proxy real world behaviors with data and data structures that turn into predictive features. Processing years of data comprised of billions of transactions to field real-time models requires the most sophisticated tech stacks in industry today using cloud computing and open-source tools like Python, Dask, and Spark to name a few.
In this role, you will:
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
The Ideal Candidate is:
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
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.
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.
Statistically-minded.You’ve built models, validated them, and backtested 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 2 years of experience in data analytics, or currently has, or is in the process of obtaining Master’s Degree, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date
At least 1 year of experience in open source programming languages for large scale data analysis
At least 1 year of experience with machine learning
At least 1 year of experience with relational databases
Preferred Qualifications:
Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
At least 1 year of experience working with AWS or other cloud computing environment
At least 2 years’ experience in Python, Scala, or R
At least 2 years’ experience with machine learning
. 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.
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