Senior Manager, Data Science
Capital One
Senior Manager, Data Science
Job Description
Overview
Senior Manager, Data Science - Commercial Data Science / AIData 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 Commercial Bank Data Science team is at the forefront of enabling Machine Learning and Generative AI capabilities within the Commercial Bank. We focus on cutting-edge AI techniques and technologies applied to Commercial Banking use cases. We work end to end from concept to production heavily focused on experimentation, predictive modeling and generative AI. The ideal candidate will be deeply passionate about AI and possess prior experience applying AI/ML in finance from a professional background.Role DescriptionIn this role, you will:Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver high impact AI infused transformations to the Commercial Bank
Leverage a broad stack of technologies — Python, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning and generative AI solutions through all phases of development, from design through training, evaluation, validation, and implementation
Mine for real time insights hidden in large internal and external datasets to help Capital One and our customers make crucial business decisions.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
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.
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 7 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 5 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) plus 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases
Masters / PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data science / AI in Finance or Banking
At least 1 year of experience working with AWS
At least 1 year of experience managing people
At least 5 years’ experience in Python, Scala, or R for large scale data analysis
At least 5 years’ experience with machine learning
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 McLean, VirginiaMcLean
Salary
80,000 - 135,000 USD / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- Generative AIintermediate
- Pythonintermediate
- AWSintermediate
- Sparkintermediate
- Statistical Modelingintermediate
- Data Analysisintermediate
- Predictive Modelingintermediate
Required Qualifications
- Bachelor's Degree in quantitative field + 7 years data analytics experience (experience)
- Master's Degree in quantitative field or MBA with quantitative concentration + 5 years data analytics experience (experience)
- PhD in quantitative field + 2 years data analytics experience (experience)
- At least 2 years open source programming for large scale data analysis (experience)
- At least 2 years machine learning experience (experience)
- At least 2 years relational databases experience (experience)
- Masters/PhD in STEM + 4 years data science/AI in Finance or Banking (preferred) (experience)
- At least 1 year AWS experience (preferred) (experience)
- At least 1 year managing people (preferred) (experience)
- At least 5 years Python/Scala/R for large scale data analysis (preferred) (experience)
Responsibilities
- Partner with cross-functional team to deliver AI transformations to Commercial Bank
- Leverage Python, AWS, Spark to analyze huge volumes of numeric and textual data
- Build machine learning and generative AI solutions from design through implementation
- Mine real-time insights from large internal and external datasets for business decisions
- Translate complex work into tangible business goals
- Research and evaluate emerging AI technologies
Benefits
- general: Comprehensive health benefits
- general: Financial benefits
- general: Other benefits supporting total well-being
Answer 10 quick questions to check your fit for Senior Manager, Data Science @ Capital One.
Related Books and Jobs
Senior Manager, Data Science
Capital One
Senior Manager, Data Science
Job Description
Overview
Senior Manager, Data Science - Commercial Data Science / AIData 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 Commercial Bank Data Science team is at the forefront of enabling Machine Learning and Generative AI capabilities within the Commercial Bank. We focus on cutting-edge AI techniques and technologies applied to Commercial Banking use cases. We work end to end from concept to production heavily focused on experimentation, predictive modeling and generative AI. The ideal candidate will be deeply passionate about AI and possess prior experience applying AI/ML in finance from a professional background.Role DescriptionIn this role, you will:Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver high impact AI infused transformations to the Commercial Bank
Leverage a broad stack of technologies — Python, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning and generative AI solutions through all phases of development, from design through training, evaluation, validation, and implementation
Mine for real time insights hidden in large internal and external datasets to help Capital One and our customers make crucial business decisions.
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
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.
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 7 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 5 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) plus 2 years of experience performing data analytics
At least 2 years of experience leveraging open source programming languages for large scale data analysis
At least 2 years of experience working with machine learning
At least 2 years of experience utilizing relational databases
Masters / PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data science / AI in Finance or Banking
At least 1 year of experience working with AWS
At least 1 year of experience managing people
At least 5 years’ experience in Python, Scala, or R for large scale data analysis
At least 5 years’ experience with machine learning
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 McLean, VirginiaMcLean
Salary
80,000 - 135,000 USD / yearly
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- Generative AIintermediate
- Pythonintermediate
- AWSintermediate
- Sparkintermediate
- Statistical Modelingintermediate
- Data Analysisintermediate
- Predictive Modelingintermediate
Required Qualifications
- Bachelor's Degree in quantitative field + 7 years data analytics experience (experience)
- Master's Degree in quantitative field or MBA with quantitative concentration + 5 years data analytics experience (experience)
- PhD in quantitative field + 2 years data analytics experience (experience)
- At least 2 years open source programming for large scale data analysis (experience)
- At least 2 years machine learning experience (experience)
- At least 2 years relational databases experience (experience)
- Masters/PhD in STEM + 4 years data science/AI in Finance or Banking (preferred) (experience)
- At least 1 year AWS experience (preferred) (experience)
- At least 1 year managing people (preferred) (experience)
- At least 5 years Python/Scala/R for large scale data analysis (preferred) (experience)
Responsibilities
- Partner with cross-functional team to deliver AI transformations to Commercial Bank
- Leverage Python, AWS, Spark to analyze huge volumes of numeric and textual data
- Build machine learning and generative AI solutions from design through implementation
- Mine real-time insights from large internal and external datasets for business decisions
- Translate complex work into tangible business goals
- Research and evaluate emerging AI technologies
Benefits
- general: Comprehensive health benefits
- general: Financial benefits
- general: Other benefits supporting total well-being
Answer 10 quick questions to check your fit for Senior Manager, Data Science @ Capital One.
Related Books and Jobs