Manager, Data Scientist – US Card (Business Card & Payments Fraud)

Job Description

OverviewManager, Data Scientist – US Card (Business Card & Payments Fraud)Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. Team DescriptionThe Business Cards and Payments Fraud Modeling team is looking for a leader to own the data science strategy for this critical business segment. This role will coordinate directly with business leadership to understand unique fraud risks and architect effective modeling solutions. You will be responsible for leading initiatives to align these models with our core Card Fraud ecosystem and spearheading the development of novel feature inputs.

Role DescriptionIn this role, you will:Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers loveLeverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual dataBuild machine learning models through all phases of development, from design through training, evaluation, validation, and implementationFlex your interpersonal skills to translate the complexity of your work into tangible business goalsThe 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. 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.

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 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 6 years of experience performing data analyticsA 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 4 years of experience performing data analyticsA PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analyticsAt least 1 year of experience leveraging open source programming languages for large scale data analysisAt least 1 year of experience working with machine learningAt least 1 year of experience utilizing relational databasesPreferred Qualifications:PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analyticsAt least 1 year of experience working with AWSAt least 4 years’ experience in Python, Scala, or R for large scale data analysisAt least 4 years’ experience with machine learningAt least 4 years’ experience with SQLCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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