Senior Associate, Data Science - Commercial Pricing

Key Skills

AWS, Conda, Data Analysis, Database, Deep Learning, ETL frameworks, H2O, Java Programming, Machine learning techniques, Mathematics, Python Programming, R Programming, Scala Programming, SPARK Programming, SQL

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.

The Commercial Banking pricing team develops and maintains the commercial pricing model for business use. The model is a core part of the deal approval process by estimating marginal profitability for new loans or deposits. It mirrors the drivers of profitability in the reported P&L, with some differences given the focus on marginal decision-making. Capital One’s Commercial Bank contains an approximately $132B (exposure) loan portfolio that has grown by virtue of several acquisitions. It is a Commercial Portfolio of Corporate Banking, Commercial Real Estate, Construction, Financial Institutions lending, and various other specialty lending.

This Sr. Associate will be part of the Commercial Pricing team which delivers customer experiences for users of business features, maintains business data subject matter expertise, up-to-date compliant logic, and well-governed features. The role will require a hybrid skill set of good machine learning techniques, strong data analysis and data engineering skills, familiarity with modeling and ETL process, and the goal of becoming a commercial subject matter expert.

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, H2O, Spark, 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.
• 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.
• 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:

• Bachelor’s Degree plus 2 years of experience in data analytics, or Master’s Degree, or PhD
• At least 1 year of experience in open source programming languages for large scale data analysis
• At least 1 year of experience with machine learning
• At least 1 year of experience with relational databases

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• Experience working with AWS
• At least 2 years’ experience in Python, Scala, or R
• At least 2 years’ experience with machine learning
• At least 2 years’ experience with SQL 
• At least 1 year’s experience in ETL 

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.