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In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models to challenge “champion models” that are deployed in production today
Flex your interpersonal skills to present how model risks could impact the business to executives
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.
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 4 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 2 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 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 1 year of experience working with Generative AI
At least 3 years’ experience in Python, Scala, or R for large scale data analysis
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
At least 3 years’ experience building or validating models to detect financial crimes (Fraud Detection, Anti-Money Laundering)
. 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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