Job Specifications
Principal Associate, Data Scientist - US Card Upmarket Acquisition
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 US Card Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions and management of new and existing credit card customers. We collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter.
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, from idea to implementation. This includes designing and executing experiments, developing and iterating on machine learning models, and deploying production-ready solutions that directly impact business outcomes.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
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 and deploying production-ready 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.
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 a Bachelor's Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master's Degree plus 3 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 1 years' experience in open source programming languages for large scale data analysis
At least 1 years' experience with machine learning
At least 1 years' experience with relational databases
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 for large scale data analysis
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.Chicago, IL: $144,200 - $164,600 for Princ Associate, Data ScienceMcLean, VA: $158,600 - $181,000 for Princ As