Principal Associate, Data Scientist - US Card Upmarket Acquisition
Capital One
Principal Associate, Data Scientist - US Card Upmarket Acquisition
Job Description
Overview
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 DescriptionThe US Card Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions and management of new and existing credit card customers. We collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter. Role DescriptionIn 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, from idea to implementation. This includes designing and executing experiments, developing and iterating on machine learning models, and deploying production-ready solutions that directly impact business outcomes.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Statistically-minded. You’ve 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, and deep learning.
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing and deploying production-ready data science solutions using open-source tools and cloud computing platforms.
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date
At least 1 years’ experience in open source programming languages for large scale data analysis
At least 1 years’ experience with machine learning
At least 1 years’ experience with relational databases
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 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R for large scale data analysis
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.comCapital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Locations
- McLean, Virginia, United States
- Chicago, Illinois McLean, VirginiaMcLean
Salary
50,000 - 85,000 USD / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Python, Scala, R for data analysisintermediate
- Machine learningintermediate
- SQL and relational databasesintermediate
- AWSintermediate
- Statistical modelingintermediate
- Data science tools (H2O, Spark)intermediate
Required Qualifications
- Bachelor’s Degree plus 5 years data analytics experience, or Master’s plus 3 years, or PhD plus 1 year (experience)
- At least 1 year open source programming for large scale data analysis (experience)
- At least 1 year machine learning experience (experience)
- At least 1 year relational databases experience (experience)
Responsibilities
- Partner with cross-functional teams to deliver products
- Build machine learning models from idea to implementation
- Leverage technologies like Python, AWS, Spark for data insights
- Design and execute experiments
- Deploy production-ready data science solutions
Benefits
- general: Comprehensive health, financial, and other benefits
Answer 10 quick questions to check your fit for Principal Associate, Data Scientist - US Card Upmarket Acquisition @ Capital One.
Principal Associate, Data Scientist - US Card Upmarket Acquisition
Capital One
Principal Associate, Data Scientist - US Card Upmarket Acquisition
Job Description
Overview
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 DescriptionThe US Card Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions and management of new and existing credit card customers. We collaborate closely with a wide range of cross functional partner teams - data engineers, platforms engineers, product managers, credit and business analysts, to deliver the solutions from ideation to implementation. We are a team of model developers, who own the full life cycle of our models - development, deployment, monitoring, governance, and ongoing usage expansion and releases. We are also a team of creative problem solvers, who challenge the status quo on a continuous basis and are devoted to innovation to keep making our models more dynamic, adaptive, robust, and ultimately, smarter. Role DescriptionIn 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, from idea to implementation. This includes designing and executing experiments, developing and iterating on machine learning models, and deploying production-ready solutions that directly impact business outcomes.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Statistically-minded. You’ve 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, and deep learning.
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing and deploying production-ready data science solutions using open-source tools and cloud computing platforms.
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.
Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years of experience in data analytics, or currently has, or is in the process of obtaining PhD plus 1 year of experience in data analytics, with an expectation that required degree will be obtained on or before the scheduled start date
At least 1 years’ experience in open source programming languages for large scale data analysis
At least 1 years’ experience with machine learning
At least 1 years’ experience with relational databases
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 1 year of experience working with AWS
At least 3 years’ experience in Python, Scala, or R for large scale data analysis
At least 3 years’ experience with machine learning
At least 3 years’ experience with SQL
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.comCapital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Locations
- McLean, Virginia, United States
- Chicago, Illinois McLean, VirginiaMcLean
Salary
50,000 - 85,000 USD / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Python, Scala, R for data analysisintermediate
- Machine learningintermediate
- SQL and relational databasesintermediate
- AWSintermediate
- Statistical modelingintermediate
- Data science tools (H2O, Spark)intermediate
Required Qualifications
- Bachelor’s Degree plus 5 years data analytics experience, or Master’s plus 3 years, or PhD plus 1 year (experience)
- At least 1 year open source programming for large scale data analysis (experience)
- At least 1 year machine learning experience (experience)
- At least 1 year relational databases experience (experience)
Responsibilities
- Partner with cross-functional teams to deliver products
- Build machine learning models from idea to implementation
- Leverage technologies like Python, AWS, Spark for data insights
- Design and execute experiments
- Deploy production-ready data science solutions
Benefits
- general: Comprehensive health, financial, and other benefits
Answer 10 quick questions to check your fit for Principal Associate, Data Scientist - US Card Upmarket Acquisition @ Capital One.