Data Scientist, Bank Marketing, Principal Associate

802 Delaware Avenue (18052), United States of America, Wilmington, Delaware

At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.

Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Data Scientist, Bank Marketing, Principal Associate

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 Bank Marketing Data Science team builds the machine learning models that help our customers learn about the great products and experiences we have to offer. We do supervised learning and reinforcement learning using tech stacks AWS, Airflow, Python, and Spark.

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, Docker, AWS, Airflow, 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, implementation, monitoring, and rapid refit
  • Flex your interpersonal skills to translate the complexity of your work into tangible business results that win more customers' business


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.
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. Your 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.


Basic Qualifications:
  • Bachelor's Degree plus 4 years of experience in data analytics, or Master's Degree plus 2 years of experience in data analytics, or PhD
  • At least 2 years' experience in open source programming languages for large scale data analysis
  • At least 2 years' experience with machine learning
  • At least 2 years' experience with relational databases


Preferred Qualifications:
  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics)
  • At least 1 year of experience working with AWS
  • At least 4 years' experience in Python, Scala, or R for large scale data analysis
  • At least 4 years' experience with machine learning
  • At least 4 years' experience with SQL


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


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