Oct 11, 2019

Principal Associate, Data Science- Bank Operations

  • Capital One
  • Wilmington, DE, USA
Full time Data Science

Job Description

Team Description

The Bank Operations Data Science team builds the machine learning models that run the gamut. We ensure our customers have access to ATMs to withdrawal their funds and deposit them at any hour of the day. Our OCR text parsing models ensure that our bank can reliably adhere to legal requests for funds in a semi-automated fashion at scale. The machine vision models we are exploring may one day allow us to lead the industry in fraud prevention. We build innovative solutions on unstructured text utilizing emerging ML tools like Tensorflow, Tesseract, and Textractor and dabble with CRNN in conjunction with OpenCV to create models that haven’t existed before.

Role Description

In this role, you will:

  • Partner with operational partners to ensure the hurdles of the real world don’t keep our solutions from driving real business value.
  • 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:

  • 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.
  • 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:
-At least a Ph.D. OR a Master’s Degree and a minimum of 1-year experience OR a Bachelor’s Degree and a minimum of 6 years of experience
-At least 1-year experience in open source programming languages for large scale data analysis
-At least 1-year experience with machine learning
-At least 1-year experience with relational databases
-At least 1-year experience with SQL

Preferred Qualifications:
-3+ years’ experience in open source programming languages for large scale data analysis
-3+ years’ experience with machine learning
-3+ years’ experience with relational databases
-3+ years’ experience with SQL


Data Scientist