Capital One
Principal Associate, Data Science
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
As a member of the Shopping ML & Data Engineering team, you'll be joining a growth-stage line of business with a startup mindset as we build technology to save our customers money. 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 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 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). Preferred Qualifications
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. At least 3 years' experience with machine learning. At least 3 years' experience with SQL. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $144,200 - $164,600 for Principal Associate, Data Science McLean, VA: $158,600 - $181,000 for Principal Associate, Data Science New York, NY: $173,000 - $197,400 for Principal Associate, 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 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. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace.
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
As a member of the Shopping ML & Data Engineering team, you'll be joining a growth-stage line of business with a startup mindset as we build technology to save our customers money. 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 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 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). Preferred Qualifications
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. At least 3 years' experience with machine learning. At least 3 years' experience with SQL. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $144,200 - $164,600 for Principal Associate, Data Science McLean, VA: $158,600 - $181,000 for Principal Associate, Data Science New York, NY: $173,000 - $197,400 for Principal Associate, 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 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. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace.