Manager, Data Science, Customer Platforms
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 delighting a combined 52 million customers each month and empowering them to manage their financial lives digitally.
As part of Digital ML, you will work on things like:
The servicing optimization engine that anticipates customers' needs in real time and helps them manage their accounts, purchases, payments, rewards, and more
The marketing optimization engine that selects the right offer for the right customer
The experimentation engine that enables us to rigorously test new features, messaging and offers for our customers
Customer behavioral analyses (using transaction, clickstream and other data) that identify trends, patterns and relationships related to product usage
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 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 6 years of experience in data analytics, or Master's Degree plus 4 years of experience in data analytics, or PhD plus 1 year of experience in data analytics
At least 2 years' experience in open source programming languages for large scale data analysis
At least 2 years' experience with machine learning
At least 2 years' experience with relational databases
PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
At least 1 year of experience working with AWS
At least 4 years' experience in Python, Scala, or R for large scale data analysis
At least 4 years' experience with machine learning
At least 4 years' experience with SQL
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Capital One is an equal opportunity employer committed to diversity in the workplace. Capital One promotes a drug-free workplace.
All qualified applicants will receive consideration for employment without regard to gender, race, color, religion, national origin, sexual orientation, protected veteran status, or disability status.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; Newark, New Jersey Ordinance 12-1630; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.