OPT Data Science Manager Jobs
Data Science Manager jobs that sponsor OPT are competitive but real. Employers in tech, finance, and healthcare actively hire F-1 students for these roles, which typically require a STEM-designated degree. Your 12-month OPT period (or 24-month STEM extension) gives you a meaningful runway to prove your value before H-1B visa sponsorship conversations begin.
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Get Access To All JobsSenior 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:
The Credit Risk Management, Loss Forecasting and Allowance team uses the latest technologies and innovative models and data to forecast and optimize future losses associated with Capital One’s credit card portfolio. We partner with model development and software engineering teams to build predictive models and automate insight generation.
As a Data Scientist, you will focus on loss forecasting modernization and data transformation. The qualified candidate will support card loss forecasting: resilience, outlook, allowance and CCAR.
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 data
- Build statistical/machine learning models to challenge “champion models” that are deployed in production today
- Contribute to the model governance of the next generation of machine learning models
- Flex your interpersonal skills to present how model risks could impact the business to executives
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.
- 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 have experience with a wide array of methods.
- 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 2 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
Preferred Qualifications:
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- Experience working with AWS
- At least 2 years’ experience in Python, Scala, or R
- At least 2 years’ experience with machine learning
- At least 2 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: $135,600 - $154,800 for Sr Assoc, Data Science
- Richmond, VA: $123,300 - $140,700 for Sr Assoc, 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).
Senior 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:
The Credit Risk Management, Loss Forecasting and Allowance team uses the latest technologies and innovative models and data to forecast and optimize future losses associated with Capital One’s credit card portfolio. We partner with model development and software engineering teams to build predictive models and automate insight generation.
As a Data Scientist, you will focus on loss forecasting modernization and data transformation. The qualified candidate will support card loss forecasting: resilience, outlook, allowance and CCAR.
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 data
- Build statistical/machine learning models to challenge “champion models” that are deployed in production today
- Contribute to the model governance of the next generation of machine learning models
- Flex your interpersonal skills to present how model risks could impact the business to executives
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.
- 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 have experience with a wide array of methods.
- 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 2 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
Preferred Qualifications:
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- Experience working with AWS
- At least 2 years’ experience in Python, Scala, or R
- At least 2 years’ experience with machine learning
- At least 2 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: $135,600 - $154,800 for Sr Assoc, Data Science
- Richmond, VA: $123,300 - $140,700 for Sr Assoc, 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).
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Get Access To All JobsTips for Finding OPT Sponsorship as a Data Science Manager
Lead with your technical depth, not just your management experience
Hiring managers want Data Science Managers who can still speak the language of their team. Highlight Python, ML pipelines, or experimentation frameworks alongside leadership credentials. This distinction matters more than your title when visa sponsorship is on the table.
Target companies with established data science organizations
Large tech firms, financial institutions, and healthcare companies with dedicated data science teams are far more likely to sponsor OPT than early-stage startups. Look for companies with 500+ employees where data infrastructure already exists and hiring is recurring.
Disclose your OPT status early and confidently in interviews
Framing matters. Say you're authorized to work immediately on OPT with STEM extension eligibility, and that H-1B visa sponsorship would be the next step. Confident clarity reduces employer hesitation more than avoiding the conversation entirely ever could.
Quantify team outcomes to justify senior-level sponsorship investment
Employers weigh sponsorship costs against expected impact. Come prepared with metrics: model accuracy improvements, revenue attributed to data initiatives, or team size you scaled. Numbers make the sponsorship decision easier for hiring managers to defend internally.
Apply before your OPT start date to maximize your authorized window
You can apply for jobs before your OPT begins, but you cannot start working until authorization is active. Starting your job search 60 to 90 days early ensures you have time to negotiate an offer while your OPT clock is still full.
Pursue STEM OPT extension eligibility from day one of employment
If your degree qualifies as STEM-designated, file your STEM extension 90 days before your initial OPT expires. This extends your authorization by 24 months and gives sponsoring employers nearly three years to complete H-1B sponsorship without a gap in your work authorization.
Data Science Manager OPT: Frequently Asked Questions
Can I work as a Data Science Manager on OPT?
Yes, provided your job duties are directly related to your degree field. Data Science Manager roles typically qualify when your degree is in computer science, statistics, applied mathematics, or a related STEM field. Your DSO must approve your employment, and the work must be at least 20 hours per week to count toward your OPT period.
Do Data Science Manager roles typically come with H-1B sponsorship?
Many do, particularly at mid-to-large companies where data science is a core business function rather than an experimental team. Companies in fintech, enterprise software, and healthcare analytics sponsor H-1B at relatively high rates for management-level data roles. Browsing verified sponsoring employers on Migrate Mate is one of the most direct ways to focus your search on companies that have sponsored similar roles before.
Does a Data Science Manager role qualify for the STEM OPT extension?
It can, but qualification depends on your degree, not your job title. If you hold a STEM-designated degree and your Data Science Manager role requires applying STEM knowledge directly, you likely qualify. Your employer must also be enrolled in E-Verify, which is required for all STEM OPT extensions. Confirm your degree's CIP code with your DSO before filing.
What happens to my OPT if I'm laid off while working as a Data Science Manager?
You have a 60-day grace period from the date your employment ends to find a new qualifying position, transfer to a different visa status, or depart the U.S. During this window you cannot work. If you secure a new Data Science Manager role within 60 days, your authorized OPT period simply resumes. The grace period does not reset your remaining OPT time.
Is a Data Science Manager role considered a specialty occupation for H-1B purposes?
Generally yes. Data Science Manager positions typically require at least a bachelor's degree in a specific technical field like computer science, statistics, or data engineering, which meets the H-1B specialty occupation standard. However, if the role has broad generalist responsibilities that don't require a degree in a specific discipline, a sponsoring employer may face additional scrutiny from USCIS during the petition process.