Capital One is looking to leverage data science and machine learning to disrupt the credit card industry by personalizing offers, empowering underwriting decisions, and unlocking opportunities to help customers save money, time, and agony in their financial lives.
Requirements
- 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
- 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
Responsibilities
- 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.
- Own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases.
- 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.
Other
- 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
- 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.
- 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.
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
