Digital ML is the data science and machine learning team inside Capital One s Digital Products organization. We deliver real-time, personalized, intelligent customer experiences in Capital One s suite of award-winning digital products, including our website, mobile app, emails, chatbot, and beyond. We partner closely with our product and engineering teams to build the data and modeling platforms crucial to the deep understanding of customers that enables our applications to delight them by adapting to their needs.
As part of Digital ML, you will:
Explore billions of clickstream events to discover the patterns in customer behavior, and use those patterns to model key customer outcomes
Build and leverage an enterprise-wide taxonomy of customer data to optimize digital marketing initiatives
Develop the real-time models that use vast amounts of customer data to anticipate customers needs and deliver the right message 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
In Digital ML, you will work at all phases of the data science lifecycle, including:
Build machine learning models through all phases of development, from design through training, evaluation and validation, and partner with engineering teams to operationalize them 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, Scala, e.g.) to collect, explore, visualize and analyze numerical and textual data (billions of customer transactions, clicks, payments, etc.) using tools like Spark, Elasticsearch, and AWS.
The Ideal candidate will be:
Curious and creative. You thrive on bringing definition to big, undefined problems. You love asking questions, and you love pushing hard to find the answers. You re not afraid to share a new idea. You communicate clearly and effectively to share your findings with non-technical audiences.
Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms. You are not afraid of petabytes of data.
Statistically-minded. You have 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 analysis and deep learning.
Customer and product oriented. You share our passion for changing banking for good.
-Bachelor s Degree plus 2 years of experience in data analytics, or Master s Degree plus 1 year of experience in data analytics, or PhD
-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
-Master s Degree in STEM field (Science, Technology, Engineering, and Mathematics) plus 1 year of experience in data analytics, or PhD in STEM field (Science, Technology, Engineering, and Mathematics)
-At least 1 year 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
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