Manager, Data Scientist - US Card, Partnerships

Manager, Data Scientist - US Card, PartnershipsData 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 Description:The US Card Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions and management of new and existing credit card customers. We collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter.Role Description:The Data Science Manager in our Partnerships team will be an integral part of the data science group supporting our Partnerships credit card operations. This team is responsible for developing machine learning models that aid in decisions related to credit card approvals or rejections, assignments of lines and APRs, adjustments of credit limits, over-limit authorizations, and marketing throughout the customer lifecycle. Our focus is on creating high-impact models that enhance business performance while also maintaining a healthy work-life balance. We place a high value on the professional development of our associates, encouraging and requiring the adoption of cutting-edge technologies to innovate our model development processes. If you are detail-oriented, passionate about learning and applying new machine learning techniques to drive business improvements, skilled in coding, an effective communicator, and an excellent team player, we invite you to join our team.In 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: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.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 dateAt least 2 years' experience in open source programming languages for large scale data analysisAt least 2 years' experience with machine learningAt least 2 years' experience with relational databasesPreferred Qualifications:PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data scienceAt least 1 year of experience working with AWSAt least 4 years' experience in Python for large scale data analysisAt least 4 years' experience with machine learningAt least 4 years' experience with SQL

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