Capital One is looking to leverage data science and machine learning to deliver real-time, personalized, and intelligent customer experiences across their digital products, aiming to delight customers by adapting to their needs and unlocking opportunities to save them money, time, and agony in their financial lives. This includes improving customer understanding, ensuring data accuracy, fighting fraud, and enhancing business outcomes in areas like marketing and servicing.
Requirements
- At least 1 year of experience working with AWS
- At least 2 years’ experience in Python, PyTorch, Scala, or R
- At least 2 years’ experience with machine learning
- At least 2 years’ experience with SQL
- At least 2 years' experience working with natural language processing
- Experience with clustering, classification, sentiment analysis, time series, and deep learning.
Responsibilities
- Explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes
- Develop the real-time models that use vast amounts of customer data to anticipate customers’ needs and deliver the right options at the right time
- Develop the models that ensure our most important customer data is accurate, fighting fraud and other bad behavior, while enabling seamless digital experiences across all our products
- Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to improve operationalization in scalable and resilient production systems that serve 50+ million customers.
- Partner closely with a variety of business and product teams across Capital One to conduct the experiments that guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention.
- Write software (Python, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark.
Other
- 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.
- 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 back tested them. You know how to interpret a confusion matrix or a ROC curve.
- 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.
