Data Science Engineer Visa Sponsorship Jobs in Virginia
Virginia is one of the strongest states for data science engineer roles, anchored by Northern Virginia's massive technology corridor and the presence of major employers like Amazon Web Services, Leidos, Booz Allen Hamilton, and Capital One. Defense contractors, cloud computing firms, and federal agencies drive consistent demand, making Virginia a frequent source of H-1B visa sponsorship for data science engineers.
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Get Access To All JobsINTRODUCTION
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
In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition.
ROLE DESCRIPTION
In this role, you will:
- Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
- Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning models to challenge “champion models” that are deployed in production today
- Contribute to the model governance framework for the next generation of machine learning models
- Flex your interpersonal skills to present how model risks could impact the business to executives
- Validate a wide variety of models across multiple business domains within our Enterprise Services division
The Ideal Candidate is:
- 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, and you’re not afraid to learn about different aspects of Capital One’s businesses.
- 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 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, Scala, or R
- 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.
COMPENSATION
- 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.
McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science
Richmond, VA: $147,100 - $167,900 for Princ 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.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
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.com.
Capital 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).
INTRODUCTION
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
In Capital One’s Model Risk Office, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can’t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes, and develop increasingly powerful techniques to avoid their repetition.
ROLE DESCRIPTION
In this role, you will:
- Partner with a cross-functional team of data scientists, software engineers, and product managers to identify and quantify risks associated with models
- Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning models to challenge “champion models” that are deployed in production today
- Contribute to the model governance framework for the next generation of machine learning models
- Flex your interpersonal skills to present how model risks could impact the business to executives
- Validate a wide variety of models across multiple business domains within our Enterprise Services division
The Ideal Candidate is:
- 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, and you’re not afraid to learn about different aspects of Capital One’s businesses.
- 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 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, Scala, or R
- 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.
COMPENSATION
- 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.
McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science
Richmond, VA: $147,100 - $167,900 for Princ 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.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
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.com.
Capital 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).
Data Science Engineer Job Roles in Virginia
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Search Data Science Engineer Jobs in VirginiaData Science Engineer Jobs in Virginia: Frequently Asked Questions
Which companies sponsor visas for data science engineers in Virginia?
Northern Virginia's technology and defense sector produces the most H-1B filings for data science engineer roles in the state. Employers with consistent sponsorship histories include Amazon Web Services, Capital One, Leidos, Booz Allen Hamilton, Freddie Mac, and various federal IT contractors headquartered in the McLean, Reston, and Tysons corridor. Large tech firms and financial services companies tend to have established immigration programs and sponsor engineers with some regularity.
Which visa types are most common for data science engineer roles in Virginia?
The H-1B is the most common visa category for data science engineers in Virginia, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, statistics, applied mathematics, or a related field. Candidates already holding OPT or STEM OPT through universities like Virginia Tech, George Mason, or UVA often transition to H-1B sponsorship through Virginia employers. The O-1A is an option for engineers with documented exceptional achievements.
Which cities in Virginia have the most data science engineer sponsorship jobs?
Northern Virginia, particularly the cities of McLean, Reston, Arlington, and Tysons, accounts for the largest share of data science engineer sponsorship opportunities in the state, driven by its concentration of tech companies, defense contractors, and financial institutions. Richmond has a growing presence from financial services firms like Capital One and Markel. Blacksburg sees some activity tied to Virginia Tech's research ecosystem, though it is smaller in volume compared to the Northern Virginia corridor.
How to find data science engineer visa sponsorship jobs in Virginia?
Migrate Mate is built specifically for international job seekers and filters data science engineer roles in Virginia by visa sponsorship willingness, so you're not manually screening hundreds of postings. The platform surfaces employers in Northern Virginia's tech and defense corridor, Richmond's financial sector, and beyond. Because sponsorship status is verified rather than inferred, Migrate Mate saves significant time for candidates on OPT, STEM OPT, or those seeking H-1B support from a Virginia employer.
Are there any Virginia-specific considerations for data science engineers seeking sponsorship?
Virginia's Northern Virginia cluster sits within the Washington D.C. metro area, which means many employers are federal contractors with security clearance requirements. Clearance eligibility can limit sponsorship options, as some contractors require U.S. citizenship or permanent residency for cleared positions. However, unclassified data science roles at the same firms often remain open to visa sponsorship. Virginia Tech and George Mason University also feed a strong graduate pipeline that employers in the region actively recruit from, which can influence hiring timelines and competition.
What is the prevailing wage for sponsored data science engineer jobs in Virginia?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.