Sr. Associate, Data Scientist - Acquisitions - Marketing Models

Employer
Capital One
Location
McLean, Virginia
Posted
Apr 15, 2021
Closes
May 14, 2021
Ref
R110412
Function
Finance
Hours
Full Time
Center 2 (19050), United States of America, McLean, Virginia

Sr. Associate, Data Scientist - Acquisitions - Marketing Models

Senior Associate,Data Scientist,Card DS+

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

As a Data Scientist at Capital One, you'll be supporting Card DS+ through our Branded Card Acquisitions Data Science Team to help build and maintain Capital One's core models. You might be setting up automated systems to deploy and maintain the predictive models that send out all of those Capital One direct mail ads every week, working with business partners to help shape our core company strategy and enhance our valuations models, or using cutting edge machine learning techniques, new novel data sources, and unlimited computing power to squeeze better performance out of the models we use to approve or decline new credit card applicants. You will need to use every ounce of your software engineering, statistics, machine learning, communication, and strategic thinking to power the next generation of our predictive models and fuel a multi-billion dollar business.

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:
  • 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.
  • 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.
  • 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.


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


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

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