Principal Associate, Data Science

Capital One
Prince George, Virginia
Nov 19, 2020
Nov 25, 2020
Organization Type
Locations: NY - New York, United States of America, New York, New York

Principal Associate, Data Science

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 100 company and a leader in the world of data-driven decision-making.

As a Data Scientist on Capital One's People Analytics team, you'll be on the leading edge of applying analytics to talent, combining machine learning and social science to build strategies that expand Capital One's talent advantage.

Team Description

The People Analytics Center of Excellence at Capital One is a 75 person cross-functional team of analysts, consultants, and data scientists. The People Analytics Talent Assessment & Analytics team builds models that help Capital One assess and select great talent. We partner with vendors to implement world class assessment solutions for the business, as well as develop our own. We derive insights, build models and develop strategies using Python, AWS, and other open-source technology. We deliver analytics to internal customers in intelligent and real time custom web applications.

Role Description

In this role, you will:

Build models and perform analyses centered on helping Capital One assess and select great talent.

These could include:

Building custom models to assess quality of hire for a given function or more broadly, all in service of developing better candidate assessment solutions

Optimizing each aspect of our recruiting operation from assessing, selecting and hiring candidates to sourcing & engaging them.

Supporting our efforts to deploy assessment technologies using best in class fairness methods.

Leverage a broad stack of technologies - Python, AWS, GitHub RedShift, and more - to reveal the insights hidden within huge volumes of recruiting data

Build predictive models through all phases of development, from design through training, evaluation, validation, and implementation

Writing white papers that explain predictive models you have developed

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

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, NLP and deep learning.

Basic Qualifications:
  • Bachelor's Degree plus 5 years of experience in data analytics, or Master's Degree plus 3 years in data analytics, 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) 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 1 year experience with NLP
  • 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.

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