Research Data Scientist Jobs in USA with Visa Sponsorship
Research Data Scientists are strong H-1B visa candidates, the role requires a master's or PhD in statistics, computer science, or a related field, which satisfies the specialty occupation standard. Many research roles qualify for O-1 visa and EB-1 green card pathways if you have publications or peer recognition. For detailed occupation requirements, see the O*NET profile.
Find Research Data Scientist JobsOverview
Showing 5 of 5,117+ Research Data Scientist jobs
See all 5,117+ Research Data Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Research Data Scientist roles.
Get Access To All JobsAbout The Team
Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. Mitigating the frontier risks resulting from these capabilities is paramount to OpenAI’s ability to continue deploying models safely. The Preparedness team is dedicated to addressing these critical risks. Our work includes:
- Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems.
- Mitigation. Keeping misalignment safeguards, alignment tools, and on track to adequately address extreme threats that might arise in the future.
- Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework, and partnering with other staff to achieve these targets.
This is urgent, fast-paced work that has far-reaching implications for the company and for society.
About The Role
Preparedness is hiring strong technical executors to support preparations for accelerated AI development, which may culminate in recursive self-improvement. This work relies on anticipating misalignment risks that might exist in the future, but might not exist now; so it’s especially important that people in this role are tasteful and strategic. The role is wide-ranging, covering any mitigation for loss of control risk, spanning the design and implementation of better pre-deployment risk-assessment, control measures, RSI-relevant training interventions, and turning one’s technical work into established institutional practices and external-facing communications.
Below Is a Subset Of Our Focus Areas
- Scalable oversight: Establishing practices for model misbehavior monitoring and oversight which remain effective in superhuman model capability regimes, with a focus on bridging from today’s monitoring approaches to future-proof ones.
- Automated auditing: As model capabilities increase, we’ll increasingly rely on automated approaches for finding the most severe forms of model misalignments. We’ll both need to sift through large swaths of production traffic to find the most egregious misalignments, and reliably elicit tail risks before deployment.
- Rigorous monitorability: Rigorous testing and red-teaming of our measurements of model misbehavior related to loss-of-control (e.g. reward hacking, sandbagging, scheming). This includes better understanding monitorability, and e.g. preparing for potential losses of Chain-of-Thought monitorability.
- Model behavior science: Design experiments and evaluations to understand the extent to which models are problematically misaligned, or their safety-relevant capabilities lag behind dangerous capabilities. This may include training model organisms of misbehavior for behaviors not currently present in production, or training interventions to increase safety-relevant capabilities.
- Coordination and verification: Prototype technical mechanisms for verifying compliance with potential future AI safety agreements.
- AI R&D risk measurement: Track progress toward automation of technical staff to inform OpenAI’s near-term investments in alignment and security.
- Maintaining and strengthening RSI safety cases: We’re especially interested in identifying and addressing blindspots of mitigation areas which we may have missed. Generally, our team alternates between performing rigorous hypothesis-driven research and turning our insights into interventions or control systems which impact production models, with occasional support of engineering teams.
In This Role, You Will
- Carefully consider the problems OpenAI might face in the future and how to prepare for them.
- Turn an open-ended objective like “prepare for future misalignment threats” into a much more concrete direction (e.g. “stress-test monitors for scheming”) – prioritizing the work that is most useful to start right now.
- Execute quickly, building scrappy prototypes, and then improving them iteratively until they become established components of our safety pipelines.
- Secure buy-in from other staff at OpenAI when necessary, and communicate your work clearly.
- Collaborate with or manage other staff as needed, since we might need to rapidly scale to tackle these problems quickly.
You Might Thrive In This Role If You
- Are an exceptional technical executor.
- Have strong strategic and research taste: you can prioritize effectively in domains with weak feedback loops.
- Are passionate about mitigating the risks associated with recursive self-improvement.
- Are driven by a desire to do whatever work most positively impacts the future of AI development.
- Bonus: you have already done work in one of the domains listed above (ML research, AI alignment, AI verification etc).
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates.
For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Compensation Range: $295K - $445K
About The Team
Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. Mitigating the frontier risks resulting from these capabilities is paramount to OpenAI’s ability to continue deploying models safely. The Preparedness team is dedicated to addressing these critical risks. Our work includes:
- Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems.
- Mitigation. Keeping misalignment safeguards, alignment tools, and on track to adequately address extreme threats that might arise in the future.
- Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework, and partnering with other staff to achieve these targets.
This is urgent, fast-paced work that has far-reaching implications for the company and for society.
About The Role
Preparedness is hiring strong technical executors to support preparations for accelerated AI development, which may culminate in recursive self-improvement. This work relies on anticipating misalignment risks that might exist in the future, but might not exist now; so it’s especially important that people in this role are tasteful and strategic. The role is wide-ranging, covering any mitigation for loss of control risk, spanning the design and implementation of better pre-deployment risk-assessment, control measures, RSI-relevant training interventions, and turning one’s technical work into established institutional practices and external-facing communications.
Below Is a Subset Of Our Focus Areas
- Scalable oversight: Establishing practices for model misbehavior monitoring and oversight which remain effective in superhuman model capability regimes, with a focus on bridging from today’s monitoring approaches to future-proof ones.
- Automated auditing: As model capabilities increase, we’ll increasingly rely on automated approaches for finding the most severe forms of model misalignments. We’ll both need to sift through large swaths of production traffic to find the most egregious misalignments, and reliably elicit tail risks before deployment.
- Rigorous monitorability: Rigorous testing and red-teaming of our measurements of model misbehavior related to loss-of-control (e.g. reward hacking, sandbagging, scheming). This includes better understanding monitorability, and e.g. preparing for potential losses of Chain-of-Thought monitorability.
- Model behavior science: Design experiments and evaluations to understand the extent to which models are problematically misaligned, or their safety-relevant capabilities lag behind dangerous capabilities. This may include training model organisms of misbehavior for behaviors not currently present in production, or training interventions to increase safety-relevant capabilities.
- Coordination and verification: Prototype technical mechanisms for verifying compliance with potential future AI safety agreements.
- AI R&D risk measurement: Track progress toward automation of technical staff to inform OpenAI’s near-term investments in alignment and security.
- Maintaining and strengthening RSI safety cases: We’re especially interested in identifying and addressing blindspots of mitigation areas which we may have missed. Generally, our team alternates between performing rigorous hypothesis-driven research and turning our insights into interventions or control systems which impact production models, with occasional support of engineering teams.
In This Role, You Will
- Carefully consider the problems OpenAI might face in the future and how to prepare for them.
- Turn an open-ended objective like “prepare for future misalignment threats” into a much more concrete direction (e.g. “stress-test monitors for scheming”) – prioritizing the work that is most useful to start right now.
- Execute quickly, building scrappy prototypes, and then improving them iteratively until they become established components of our safety pipelines.
- Secure buy-in from other staff at OpenAI when necessary, and communicate your work clearly.
- Collaborate with or manage other staff as needed, since we might need to rapidly scale to tackle these problems quickly.
You Might Thrive In This Role If You
- Are an exceptional technical executor.
- Have strong strategic and research taste: you can prioritize effectively in domains with weak feedback loops.
- Are passionate about mitigating the risks associated with recursive self-improvement.
- Are driven by a desire to do whatever work most positively impacts the future of AI development.
- Bonus: you have already done work in one of the domains listed above (ML research, AI alignment, AI verification etc).
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates.
For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Compensation Range: $295K - $445K
See all 5,117+ Research Data Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Research Data Scientist roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Research Data Scientist
Target employers with dedicated research divisions
Tech companies, pharmaceutical firms, national labs, and universities run dedicated research functions with established H-1B sponsorship pipelines. These employers file petitions routinely and have immigration counsel in place, making the process faster and less uncertain for you.
Lead with publications and citations in your application
Research Data Scientist roles demand evidence of original contribution. A strong publication record signals you're a researcher, not just an analyst, which strengthens both the employer's sponsorship case and your long-term O-1 or EB-1 eligibility from day one.
Understand how your degree field affects H-1B eligibility
USCIS requires your degree to align with the specific research domain. A statistics degree supports a biomedical research role less cleanly than a biostatistics degree. Misalignment is a common RFE trigger, so address it directly in your cover letter and resume.
Ask about cap-exempt employer options
Universities, affiliated research institutions, and nonprofit research organizations are exempt from the H-1B lottery. If you didn't get selected in the annual cap, these employers let you start immediately without waiting for the next registration cycle.
Build a record that supports an EB-1A or NIW petition
Research Data Scientists are well-positioned for employment-based green cards. Peer-reviewed publications, conference presentations, grant awards, and peer review work all count as evidence. Start documenting these early, even before you have a sponsoring employer.
Browse Migrate Mate to find employers actively sponsoring this role
Not every company that posts a Research Data Scientist role will sponsor a visa. Migrate Mate filters jobs by sponsorship willingness, so you spend time applying to employers who have already committed to supporting international candidates in this specific field.
Frequently Asked Questions
Does a Research Data Scientist role qualify for H-1B sponsorship?
Yes. Research Data Scientist is a strong specialty occupation candidate because it requires at minimum a bachelor's degree, and typically a master's or PhD, in a specific field such as statistics, computer science, or applied mathematics. USCIS approves the majority of petitions for research-oriented data science roles at top employers, though RFEs are common when the degree field doesn't closely match the research domain.
Do I need a PhD to get sponsored as a Research Data Scientist?
Not always, but a PhD significantly improves your prospects. Many employers require a PhD for roles involving original research, model development, or publication output. A master's degree may be sufficient at companies where the role is more applied than academic. If you hold a bachelor's degree, substantial published research or equivalent work experience can compensate, but expect closer scrutiny from USCIS during the petition review.
Can a Research Data Scientist qualify for an O-1 visa instead of H-1B?
Yes, and it's often a better path if you didn't win the H-1B lottery. The O-1A visa covers individuals with extraordinary ability in sciences, and research data scientists with peer-reviewed publications, conference presentations, citations, grants, or peer review experience can meet the criteria. O-1 has no annual cap and no lottery, so qualified candidates can start work much faster than waiting for H-1B visa selection.
What green card pathway makes the most sense for Research Data Scientists?
The two strongest options are EB-1A (extraordinary ability) and EB-2 NIW (national interest waiver). EB-1A suits candidates with significant publication records, awards, or peer recognition. NIW is more accessible and fits researchers whose work has broader societal impact, such as public health, climate, or AI safety research. Both allow self-petition, meaning you don't need an employer to sponsor you, which is a major practical advantage.
Where should I look for Research Data Scientist jobs that offer visa sponsorship?
Migrate Mate is built specifically for international candidates and filters Research Data Scientist roles by employers willing to sponsor visas. This removes the guesswork of applying to postings where sponsorship is unlikely. Research-heavy employers including major tech companies, biotech firms, and university-affiliated research labs appear frequently and are among the most experienced H-1B petitioners for this role.
What is the prevailing wage requirement for sponsored Research Data Scientist jobs?
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.