Manager, Data Science - Emerging ML

Capital One•San Jose, CA

About The Position

Data is at the center of everything Capital One does, having disrupted the credit card industry in 1988 with personalized offers using statistical modeling. As a Fortune 200 company and a leader in data-driven decision-making, Capital One is now leading the next wave of disruption using the latest computing and machine learning technologies to operate across billions of customer records. As a Data Scientist, you will be part of a team focused on unlocking opportunities to help customers save money, time, and agony in their financial lives. The Emerging ML team, part of Capital One’s Applied Research organization, specializes in the research and development of new AI technologies, particularly Embeddings and Foundation Models. This team collaborates closely with product and engineering teams to integrate emerging technologies with critical business use cases across Capital One. In this individual contributor role within Emerging ML, you will engage in all phases of the data science lifecycle. This includes building machine learning models from design through training, evaluation, and validation, and then partnering with engineering teams to operationalize these models in scalable production systems for over 50 million customers. You will also work closely with various business and product teams to conduct experiments that improve customer experiences and business outcomes in areas like marketing, servicing, and fraud prevention. Additionally, you will write software using languages like Python and Scala to collect, explore, visualize, and analyze vast amounts of numerical and textual data (billions of customer transactions, clicks, payments) using tools such as Spark and AWS.

Requirements

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 (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
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 Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
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 PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing relational databases

Nice To Haves

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
Experience working with AWS
At least 4 years’ experience in Python, Scala, or R
At least 4 years’ experience with machine learning
At least 4 years’ experience with SQL

Responsibilities

Conducting research into self supervised learning, transformer models, and representation learning
Building customer behavioral models (using transaction, clickstream, and other data) that identify trends, patterns, and relationships related to product usage
Refining integration patterns for encoder and decoder models for downstream use cases to connect Applied Research products and business use cases
Build machine learning models through all phases of development, from design through training, evaluation and validation
Partner with engineering teams to operationalize machine learning models 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