Principal Data Scientist (McLean)

Principal Associate,Data Scientist -Commercial Risk Analytical Infrastructure

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

Capital One's Commercial Bank Team has a $100B+ loan portfolio that has grown organically and via acquisitions, covering C&I, CRE, and Structured Products. The infrastructure team drives innovation in commercial risk analytics by enhancing business performance and process efficiency through automation and cloud computing. The team collaborates cross-organizations with business, product and tech to build a strong foundation for model deployment and automated workflows, ensuring scalable, reliable, and efficient integration of risk models into business processes to generate powerful insights into portfolio trends and risk models.

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, 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:

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.

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.

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 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 5 years of experience performing data analytics

A 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 3 years of experience performing data analytics

A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

Master's Degree in STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in STEM field (Science, Technology, Engineering, or Mathematics)

At least 1 year of experience working with AWS

At least 3 years' experience in Python, Scala, or R

At least 3 years' experience with machine learning

At least 3 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.

McLean, VA: $158,600 - $181,000 for Princ Associate, Data Science

Principal Data Scientist

Principal Associate,Data Scientist -Commercial Risk Analytical Infrastructure

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

Capital One's Commercial Bank Team has a $100B+ loan portfolio that has grown organically and via acquisitions, covering C&I, CRE, and Structured Products. The infrastructure team drives innovation in commercial risk analytics by enhancing business performance and process efficiency through automation and cloud computing. The team collaborates cross-organizations with business, product and tech to build a strong foundation for model deployment and automated workflows, ensuring scalable, reliable, and efficient integration of risk models into business processes to generate powerful insights into portfolio trends and risk models.

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, 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:

• 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.

• 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.

• 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 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 5 years of experience performing data analytics

  • A 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 3 years of experience performing data analytics

  • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)

Preferred Qualifications:

• Master's Degree in STEM field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in STEM field (Science, Technology, Engineering, or Mathematics)

• At least 1 year of experience working with AWS

• At least 3 years' experience in Python, Scala, or R

• At least 3 years' experience with machine learning

• At least 3 years' experience with SQL

Capital One will consider sponsoring a new qualified applicant ]]> <