Capital One is looking to leverage AI and Machine Learning to drive the next wave of disruption in Commercial Banking, unlocking opportunities to help customers save money, time, and agony in their financial lives by analyzing billions of customer records.
Requirements
- Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
- Experience with clustering, classification, sentiment analysis, time series, and deep learning.
- 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
- Experience applying AI/ML in finance from either a professional or academic background.
Responsibilities
- Leverage a broad stack of technologies — Python, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning and generative AI solutions through all phases of development, from design through training, evaluation, validation, and implementation
- Mine for real time insights hidden in large internal and external datasets to help Capital One and our customers make crucial business decisions.
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver high impact AI infused transformations to the Commercial Bank
- Continuously research and evaluate emerging technologies.
- Stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
- Develop further in open-source languages.
Other
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
- Innovative. You continually research and evaluate emerging technologies.
- Creative. You thrive on bringing definition to big, undefined problems.
- Statistically-minded. You’ve built models, validated them, and backtested them.
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field plus 5 years of experience performing data analytics, A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics, A PhD in a quantitative field.
