Capital One
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Manager, Data Science - US Card (Fraud)
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Capital One 6 days ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. 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. Team Description:
The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters. We prevent fraud at many steps of a customer journey, from the application to spending and payments, using real-time models. We care very deeply about doing things the right way, automating, and innovating to improve the customer experience and prevent fraud. 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 Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: 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. 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. Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. 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. 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. Basic Qualifications: 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 6 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 4 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 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
Preferred Qualifications: PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics At least 1 year of experience working with AWS At least 4 years’ experience in Python, Scala, or R for large scale data analysis At least 4 years’ experience with machine learning At least 4 years’ experience with SQL Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Salary ranges by location (example): Chicago, IL: $175,800 - $200,700 for Mgr, Data Science McLean, VA: $193,400 - $220,700 for Mgr, Data Science New York, NY: $211,000 - $240,800 for Mgr, Data Science Richmond, VA: $175,800 - $200,700 for Mgr, Data Science 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. This role is also eligible to earn incentives. Capital One offers a comprehensive, inclusive set of health, financial and other benefits that support your total well-being. Eligibility varies based on status and level. For accommodation or recruiting questions, contact Capital One Recruiting. This role is expected to accept applications for a minimum of 5 business days. No agencies. Capital One is an equal opportunity employer (EOE, including disability/vet). Capital One does not guarantee third-party products or services advertised on this site. Capital One Financial is made up of several entities. Some postings may refer to roles in other regions. We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
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Manager, Data Science - US Card (Fraud)
role at
Capital One 6 days ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. 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. Team Description:
The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters. We prevent fraud at many steps of a customer journey, from the application to spending and payments, using real-time models. We care very deeply about doing things the right way, automating, and innovating to improve the customer experience and prevent fraud. 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 Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: 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. 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. Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. 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. 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. Basic Qualifications: 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 6 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 4 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 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
Preferred Qualifications: PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics At least 1 year of experience working with AWS At least 4 years’ experience in Python, Scala, or R for large scale data analysis At least 4 years’ experience with machine learning At least 4 years’ experience with SQL Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Salary ranges by location (example): Chicago, IL: $175,800 - $200,700 for Mgr, Data Science McLean, VA: $193,400 - $220,700 for Mgr, Data Science New York, NY: $211,000 - $240,800 for Mgr, Data Science Richmond, VA: $175,800 - $200,700 for Mgr, Data Science 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. This role is also eligible to earn incentives. Capital One offers a comprehensive, inclusive set of health, financial and other benefits that support your total well-being. Eligibility varies based on status and level. For accommodation or recruiting questions, contact Capital One Recruiting. This role is expected to accept applications for a minimum of 5 business days. No agencies. Capital One is an equal opportunity employer (EOE, including disability/vet). Capital One does not guarantee third-party products or services advertised on this site. Capital One Financial is made up of several entities. Some postings may refer to roles in other regions. We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
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