Senior Manager - Lead Data Scientist in Retail Bank Price and Policy Optimization

Center 2 (19050), United States of America, McLean, Virginia Retail Bank Price and Policy Optimization Data Science Lead - Senior Manager Data is at the heart of everything we do. We started as a disruptor in the credit card industry by individually personalizing each card offer using statistical modeling and a relational database—an advanced technology in 1988. Fast forward a few years, and our small innovation, fueled by our passion for data, has propelled us into a Fortune 200 company and a data-driven decision-making leader. As a Data Scientist at Capital One, you will be part of a team that is leading the next wave of disruption on an even greater scale. You will use the latest computing and machine learning technologies, operating across billions of customer records to identify significant opportunities to help everyday people save money, time, and hassle in their financial lives. As the price and policy optimization lead at the Retail and Direct Bank, you will join a mission-driven modeling and analytics team aiming to shape the future of banking. The Bank team is intensely focused on statistical modeling and innovation, continually improving decision-making and adding value to the business. This role offers a unique opportunity to contribute to the growth of our savings and checking portfolios by creating pricing strategies using numerical optimization and simulation techniques for company funding. Likewise, you will also optimize checking product policies to differentiate products and enhance the customer experience. Role Description In this role, you will: - Collaborate with a cross-functional team of data scientists, software engineers, and product leaders to deliver a product that customers will love - Utilize a wide range of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal insights hidden within a vast amount of numerical and textual data - Build machine learning models throughout all development phases, from design to training, evaluation, validation, and implementation, using your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: - Innovative: You consistently research and evaluate emerging technologies and stay informed about the latest methods, technologies, and applications, seeking opportunities to apply them - A Leader: You challenge conventional thinking and work with stakeholders to improve the standard. You're passionate about fostering the talent within your team - Technical: You're comfortable with open-source languages and intend to develop your skills further. You have practical experience in devising data science solutions using open-source tools and cloud-based platforms. - Statistical: You have built models, validated them, and backtested them. You can interpret a confusion matrix or a ROC curve. You have experience in clustering, classification, sentiment analysis, time series, and deep learning. Basic Qualifications: - A Bachelor’s Degree with 7 years of experience, a Master’s Degree with 5 years of experience or a PhD with 2 years of experience in data analytics - At least 3 years of experience with open-source programming languages for large scale data analysis - At least 3 years of experience with machine learning - At least 3 years of experience with relational databases Preferred Qualifications: - A PhD in "STEM" (Science, Technology, Engineering, or Mathematics) field with at least 4 years of experience in data analytics - At least 1 year of experience working with AWS - At least 1 year of experience managing people - At least 5 years of experience in Python, Scala, or R for large scale data analysis - At least 5 years of experience with machine learning - Experience using numerical optimization to solve business problems - Experience with linear, non-linear, integer programming techniques and software packages. - Successfully optimized business outcomes and decision systems - Experience formulating business issues involving complex data, models, and policy rules - Experience working with time-series models - Ability to collaborate with business leads and communicate models and methods clearly Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Capital One offers a comprehensive, inclusive, and competitive set of health, financial, and other benefits that support your total well-being. Please visit the Capital One Careers website for more information. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. Capital One promotes a drug-free workplace. If you require an accommodation during the application or interview process, please contact the Capital One Recruiting team at 1-800-304-9102 or via email at [email protected]. For technical support or questions about Capital One's recruitment process, please send an email to [email protected]. Capital One does not provide, endorse, or guarantee third-party products, services, or educational tools, and is not liable for such information available through this site. Capital One Financial is made up of several different entities, so please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe, and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).