Principal Associate, Data Scientist - US Card; Credit Team

Principal Associate, Data Scientist - US Card (New To Credit Team)

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 New to Credit Data Science team develops machine learning models for marketing, risk, and valuation. These models help our business partners make informed marketing and underwriting decisions throughout the credit card lifecycle. We prioritize advanced modeling techniques, alternative data sources, and robust infrastructure to enhance decision accuracy and efficiency. Additionally, we conduct thorough statistical analysis to generate insights that influence various business strategies.

You will collaborate with data scientists, business analysts, and software engineers on all stages of model development. This work will be conducted in a supportive environment that values your contributions, encourages new responsibilities, promotes ongoing learning, and rewards innovation.

Role Description

In this role, you will:

• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

• Leverage a broad stack of technologies - Python, Conda, AWS, Spark, Kubeflow Pipelines, and more - to reveal the insights hidden within huge volumes of numeric and textual data

• Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love

• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

• 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.

• 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.

• 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.

• 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.

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 industry experience in data science, or PhD in "STEM" field (Science,…