Capital One
Financial Services
Manager,DataScience
Neural analysis suggests this role is
optimal for Manager candidates.
“Manager, Data Science at Capital One. Skills: Data Science, Machine Learning, Statistical Modeling, Python, Scala, Spark, AWS. 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”
What You'll Achieve.
Unlock big opportunities that help everyday people save money, time and agony in their financial lives; Operationalize models in scalable and resilient production systems that serve 50+ million customers; Guide improvements to customer experiences and business outcomes in domains like marketing, servicing and fraud prevention
Industry & Context.
Unlocking big opportunities; Identifying trends, patterns, and relationships; Guiding improvements to customer experiences and business outcomes
What They're Looking For.
Must Have
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, 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, 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 Have
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
What You'll Do.
Conducting research into self supervised learning
and representation learning
Building customer behavioral models (using transaction
and other data) that identify trends
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 models in scalable and resilient production systems
Conduct experiments that guide improvements to customer experiences and business outcomes
Write software to collect
visualize and analyze numerical and textual data
How You'll Work.
Team & Collaboration
Partner closely with product and engineering teams to connect emerging technologies with business critical use cases; Partner closely with a variety of business and product teams across Capital One; Partner with engineering teams to operationalize models
Communication Scope
Communicate clearly and effectively to share findings with non-technical audiences
Full Job Description
Manager, Data Science - Emerging ML Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. **Team Description** Emerging ML is the data science and machine learning team inside Capital One’s Applied Research organization. We focus on research and development of new technologies within the domain of Artificial Intelligence with a focus on Embeddings and Foundation Models. We partner closely with our product and engineering teams to connect emerging technologies with business critical use cases across Capital One’s lines of business. As part of Emerging ML, you will work on things like: * 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 **Role Description** This is an individual contributor position. In Emerging 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 part
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