Director, Data Scientist

Director, Data ScientistData 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 Generative AI Systems (Genesis) team within Card Data Science builds state-of-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time-series sequencing modeling. We partner with product, tech and design teams to deliver internal applications based on these solutions that drive efficiency in our business and data analytics teams, as well as customer-facing applications that enhance the customer experience. You will lead a seasoned group of natural language processing (NLP), speech, and computer vision specialists, experimenting with emerging technologies in generative AI, delivering software implementing these technologies, and contributing research to major NLP and AI/ML conferences.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, Kubernetes, 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.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.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 9 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 7 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 4 years of experience performing data analyticsAt least 4 years of experience leveraging open source programming languages for large scale data analysisAt least 4 years of experience working with machine learningAt least 4 years of experience utilizing relational databasesPreferred Qualifications:PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analyticsAt least 1 year of experience working with AWSAt least 3 years of experience managing peopleAt least 5 years of experience in Python, Scala, or R for large scale data analysisAt least 5 years of experience with machine learningCapital One will consider sponsoring a new qualified applicant for employment authorization for this position.The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.McLean, VA: $269,100 - $307,200 for Dir, Data ScienceNew York, NY: $293,600 - $335,100 for Dir, Data ScienceCandidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace.