Principal Associate, Data Scientist - Retail Bank Valuations Data Science
About The Position
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 The Marketing & Valuations Data Science Team in the Retail Bank builds models that improve marketing efficiency and drive account growth via intelligent targeting, measurement, segmentation, and customer value modeling. We do data and model pipelining, machine learning, and well-managed model operations using Python and ML libraries in our tech stacks. If you enjoy the challenge of creating best-in-class solutions that provide long term value in a rapidly changing space, this is the role for you. Role Description In this role you will be building the next generation of customer valuations models for the Retail Bank that improve marketing efficiency and drive account growth via intelligent targeting, measurement, and segmentation. In this role, you will: Work closely with subject matter experts to deliver flexible, well managed models that perform well under a variety of economic conditions Translate business goals into data science solutions and communicate with senior stakeholders Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation Explore next-generation model architectures (e.g. embeddings, sequence models) to unlock value in our marketing efficiency
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 5 years of experience performing data analytics
- 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 3 years of experience performing data analytics
- A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field)
Nice To Haves
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- At least 3 years’ experience in Python
- At least 3 years’ experience with machine learning, including XGBoost
- At least 3 years’ experience with SQL
- At least 1 year’s experience in open source programing languages for large scale data analysis
- Experience with next-generation model architectures such as embeddings, sequence models
Responsibilities
- Work closely with subject matter experts to deliver flexible, well managed models that perform well under a variety of economic conditions
- Translate business goals into data science solutions and communicate with senior stakeholders
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Explore next-generation model architectures (e.g. embeddings, sequence models) to unlock value in our marketing efficiency
Benefits
- comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
- performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
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What This Job Offers
Job Type
Full-time
Career Level
Principal
