Capital One is looking to protect its customers from fraudsters by building and maintaining machine learning models that detect fraudulent activity. The company aims to leverage data-driven decision-making and cutting-edge machine learning technologies to unlock opportunities that help customers save money, time, and agony in their financial lives.
Requirements
- 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
- At least 1 year of experience working with AWS
- 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
Responsibilities
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- 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
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
- Build, maintain, and manage models using a tech stack of Python, Spark, and Kubernetes
- Retrieve, combine, and analyze data from a variety of sources and structures
- Develop data science solutions using open-source tools and cloud computing platforms
- Continuously research and evaluate emerging technologies and stay current on published state-of-the-art methods, technologies, and applications
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, with an expectation that required degree will be obtained on or before the scheduled start date
- 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.
- 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.
- Technical. You’re comfortable with open-source languages and are passionate about developing further.
- 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.
