Manager, Data Science - Fraud, Deep Learning

About Capital One

Over 25 years ago, Capital One revolutionized the credit card industry with data and technology. Today, we are one of the most widely recognized brands in banking — serving more than 100 million customers across a diverse set of businesses.

Position

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, Tensorflow 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.

Your qualification

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, Tensorflow 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

What we offer

Your wellbeing is our priority

Our benefits and total compensation package is designed for the whole person. Caring for both you and your family

• Healthy Body, Healthy Mind

You have options and we have the tools to help you decide which health plans best fit your needs

• Save Money, Make Money

Secure your present, plan for your future and reduce expenses along the way

• Time, Family and Advice

Options for your time, opportunities for your family, and advice along the way. It's time to BeWell.

Additional details

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

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.