Data Scientist Intern - Johns Hopkins University
As a Data Scientist at Capital One, you’ll be part of a high-performing team that’s embracing the latest in computing technologies to unlock opportunities that help everyday people save money and improve their financial lives.
You'll help our customers solve their financial services challenges by using groundbreaking techniques. You'll make valuable contributions from day one by continuously learning, engaging in diverse sets of experiences and building close-knit relationships across the company.
On any given day you might:
• Evaluate open source and internally-developed modeling and analytics tools using real business data
• Integrate internal data with external data sources and APIs to discover actionable insights
• Design and craft rich data visualizations to extract insights and communicate stories to customers and company leadership
We'd love to find someone who is…
1. Curious. You ask why, you explore, and you are excited to imagine and create new ideas by inventing self-adaptive models or by tapping into unstructured data sources. You're also excited to try new tools or technologies.
2. Data Savvy. You are passionate about moving data from a database or an API and transforming it into everyday language.
3. A do-er. You love trying new things, even if you sometimes fail.
Are you ready to join a community of people like you - ones who embrace customer problems and use their passion and capabilities to make a difference every single day?
• Have obtained or will obtain a master’s or PhD degree in a quantitative field of study between December 2017 and August 2018 from Johns Hopkins University
• At least 6 months of experience or course work in open source programming languages for data analysis
• At least 6 months of experience or course work in inferential statistics or machine learning
• Direct experience with either Python or R, plus one other general purpose programming language such as Java or C/C++
• Experience or course work with relational databases
• Experience or course work with large scale data analysis