Principal Associate, Data Science - Credit Risk Management

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Center 2 (19050), United States of America, McLean, Virginia

Principal Associate, Data Science - Credit Risk Management

Job Description

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 Credit Risk Management, Loss Forecasting and Allowance team uses machine learning models to forecast and optimize future losses associated with Capital One’s credit card portfolio. We work with the Center of Machine Learning to use the latest technologies and algorithms to build predictive models and automate insight generation.

As a Data Scientist, you will focus on loss forecasting modernization, data transformation and cyber remediation. The qualified candidate will support card loss forecasting: resilience, outlook, allowance and CCAR.

Role Description

In this role, you will:

• 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,, Spark, Dask and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Build machine learning model pipelines through all phases of development, from design through training, evaluation, validation, and implementation
• Leverage the knowledge of technology and statistics to present results in a format that can be easily explained to leadership
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The 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.
• 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.
• 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.
• 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 phase 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:

• At least a PhD OR a Master’s Degree and a minimum of 1 year experience OR a Bachelor’s Degree and a minimum of 6 years of experience
• At least 1 year experience in open source programming languages for large scale data analysis
• At least 1 year experience with machine learning
• At least 1 year experience with relational databases
• At least 1 year experience with SQL

Preferred Qualifications:

• 3+ years’ experience in open source programming languages for large scale data analysis
• 3+ years’ experience with machine learning
• 3+ years’ experience with relational databases
• 3+ years’ experience with SQL

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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, race, color, age, national origin, religion, physical and mental disability, genetic information, marital status, sexual orientation, gender identity/assignment, citizenship, pregnancy or maternity, protected veteran status, or any other status prohibited by applicable national, federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.