Principal Associate, Data Scientist
Retail Bank
PrincipalAssociate,DataScientist-RetailBank
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“Principal Associate, Data Scientist - Retail Bank at Principal Associate, Data Scientist. Skills: Data Science, Machine Learning, Statistical Modeling, Python, AWS. Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. Leverage a broad stack of technologies to reveal the insights hidden within huge volumes of numeric and textual data”
What You'll Achieve.
Deliver a product customers love; Unlock the big opportunities that help everyday people save money, time and agony in their financial lives
Industry & Context.
Bring definition to big, undefined problems; Ask hard questions and push hard to find answers
What They're Looking For.
Must Have
Bachelor's Degree plus 2 years of experience in data analytics, Master's Degree, 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
Nice to Have
Master's Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), PhD in “STEM” field (Science, Technology, Engineering, or Mathematics), Experience working with AWS, At least 2 years’ experience in Python, Scala, or R, At least 2 years’ experience with machine learning, At least 2 years’ experience with SQL
What You'll Do.
Build machine learning models through all phases of development
from design through training
Leverage a broad stack of technologies to reveal the insights hidden within huge volumes of numeric and textual data
Identify when we fail to help our customers
when our customers are satisfied
and further help our bank identify process failures
Forecasting all of the cash needs of our customers
Identifying potential issues and providing an interpretable output that front line agents can use to better help meet our customers’ needs
How You'll Work.
Team & Collaboration
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
Communication Scope
Translate the complexity of your work into tangible business goals
Full Job Description
Principal Associate, Data Scientist - Retail Bank 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 back office of the future will help identify when we fail to help our customers, when our customers are satisfied, and further help our bank identify process failures. That future is already occurring. If you enjoy building and working with light web applications while forecasting all of the cash needs of our customers then a position on the Bank Operations Data Science team is the right spot for you. Our solutions run the gamut from basic time series forecasting to advanced optimization and focus on not only identifying potential issues but providing an interpretable output that front line agents can use to better help meet our customers’ needs. **Role Description** ****In this role, you will:**** * Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love * Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data * Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation * Fl
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