Manager, Data Science, Model Risk Office

Center 1 (19052), United States of America, McLean, Virginia Manager, Data Science, Model Risk Office Data is at the heart of what we do. As a startup, we disrupted the credit card industry by tailoring every credit card offer using statistical modeling and the relational database, revolutionary technology for 1988! A few years later, this small innovation and our enthusiasm for data launched us into being a Fortune 200 company and a global leader in data-driven decision-making. As a Data Scientist at Capital One, you will be part of a team that is spearheading the next wave of disruption on an unprecedented scale, using the latest in computing and machine learning technologies and working across billions of customer records to unveil significant opportunities that aid everyday people in saving money, time and hassle in their financial lives. Team Description: At Capital One’s Model Risk Office, we safeguard the company against model failures and explore new ways to make superior decisions with models. We utilize our expertise in statistics, software engineering, and business to drive optimal outcomes in both Risk Management and the Enterprise. We understand that we cannot prepare for the future by focusing on the present, so we invest in what is to come: developing new skills, constructing enhanced tools, and sustaining a network of trusted partners. We learn from past mistakes and devise increasingly effective strategies to prevent their recurrence. Role Description: In this role, you will: - Collaborate with a multi-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models - Utilize a wide range of technologies — Python, Conda, AWS, Spark, and more — to uncover insights hidden within vast volumes of numeric and textual data - Construct machine learning models to challenge the “champion models” that are currently in production - Contribute to the governance of the next generation of machine learning models - Exercise your interpersonal skills to present how model risks could impact the business to company executives The Ideal Candidate is: - Innovative. Keeps up with emerging technologies and applies state-of-the-art methods, technologies, and applications. - Creative. Excels in defining big, undefined problems, questioning and pushing for answers and not scared to present a new idea. - Technical. Familiar with open-source languages and eager to advance further. Has hands-on experience in developing data science solutions using open-source tools and cloud computing platforms. - Statistically-minded. Has built, validated and tested models. Can interpret a confusion matrix or a ROC curve and has experience in clustering, classification, sentiment analysis, time series, and deep learning. - A data expert. Not intimidated by “Big data” and has the skills to retrieve, integrate and analyze data from various sources and structures. Understood that understanding data is key to great data science. Basic Qualifications: - Has, or is in the process of acquiring a Bachelor’s Degree, alongside 6 years of experience in data analytics, or has, or is in the process of acquiring a Master’s Degree along with 4 years of experience in data analytics, or has, or is in the process of acquiring a PhD along with one year of experience in data analytics. - Has at least 2 years’ experience with machine learning - Has at least 2 years’ experience with relational databases Preferred Qualifications: - Possesses a PhD in a “STEM” field (Science, Technology, Engineering, or Mathematics) with 3 years of experience in data analytics - Has at least one year of experience working with AWS - Has at least 4 years’ experience in Python, Scala, or R for large scale data analysis - Has at least 4 years’ experience with machine learning - Has at least 4 years’ experience with SQL - Has at least 4 years’ experience building or validating models to detect financial crimes (Fraud Detection, Anti-Money Laundering) Note: Capital One will contemplate sponsoring a new eligible applicant for employment authorization for this position. Capital One offers a comprehensive, competitive, and inclusive range of health, financial and other benefits that support your overall well-being. For more information, please visit the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. Please note, agencies need not apply. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualifying applicants will receive consideration for employment without bias towards gender, 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 grounds prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace and adheres to the requirements of relevant laws concerning criminal background enquiries. If you have visited our website for information on employment opportunities or to apply for a position, and you require an accommodation, please call Capital One Recruiting at 1-800-304-9102 or email at [email protected]. Any information you provide will be kept confidential and will be used only to provide required reasonable accommodations. For issues about Capital One's recruiting process, please send an email to [email protected]. Please note that Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or any other information available through this site. Capital One Financial comprises several different entities. Please understand that any position posted in Canada, the United Kingdom, or the Philippines corresponds to Capital One Canada, Capital One Europe, and Capital One Philippines Service Corp. (COPSSC) respectively.