Manager, Data Science - Fraud, Deep Learning

Location: Pimmit Hills 11 West 19th Street (22008), United States of America, New York, New York Manager, Data Science - Fraud, Deep Learning Manager, Data Scientist, 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 Description The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters. We prevent fraud at many steps of a customer journey, from the application to spending and payments, using real-time models. We care very deeply about doing things the right way, automating, and innovating to improve the customer experience and prevent fraud. In this role, you will: Utilize Deep Learning and Sequence Modelling techniques to build Fraud models Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, Pytorch, Tensor flow and more — to reveal the insights hidden within huge volumes of numeric and textual data Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Flex your interpersonal skills to translate the complexity of your work into tangible business goals The 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. 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 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 date At least 2 years’ experience in open source programming languages for large scale data analysis At least 2 years’ experience with machine learning At least 2 years’ experience with relational databases Preferred Qualifications: At least 1 year of experience working with AWS At least 2 years’ experience building advanced Deep Learning architectures (for example: RNN’s, CNN’s, Transformers) At least 2 years’ experience with Pytorch, Tensor flow or other Deep Learning frameworks At least 4 years’ experience in Python, Scala, or R for large scale data analysis At least 4 years’ experience with machine learning At least 4 years’ experience with SQL Capital 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. New York City (Hybrid On-Site): $201,400 - $229,900 for Mgr, Data Science Candidates 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…