Principal Research Scientist Visa Sponsorship Jobs in New York
Principal research scientist visa sponsorship jobs in New York draw top talent to institutions like IBM Research, Memorial Sloan Kettering, Rockefeller University, and Cold Spring Harbor Laboratory. From Manhattan's biotech corridor to Long Island's research campuses, New York's depth in life sciences, artificial intelligence, and materials science makes it one of the most active states for sponsored research roles.
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Do you want to define the scientific direction for how a global contact-center network forecasts demand, schedules its workforce, and optimizes operations in real time? The Eliza team within Amazon Connect (FCS) is looking for a Principal Research Scientist with a deep operations research specialization to set the research agenda in operations science — combinatorial optimization, queueing theory, stochastic modeling, and forecasting — and to translate that research into production systems that serve millions of customer interactions.
As a Principal Research Scientist, you will be the senior technical voice for operations research across the org. You will identify the highest-leverage scientific problems, architect novel solutions, and drive them from research through production deployment. You will not sit apart from the work — you will remain deeply hands-on with data, models, and systems while raising the scientific bar for scientists and engineers around you. This is an individual-contributor Principal role: your influence comes from technical depth, invention, and the ability to move business and engineering roadmaps through scientific rigor.
You will operate at the intersection of demand forecasting, workforce scheduling, and network optimization — applying combinatorial optimization to large-scale scheduling and resource-allocation problems and queueing theory to model contact-center dynamics under uncertainty, non-stationarity, and competing operational constraints at Internet scale — turning that reasoning into systems that continuously sense, predict, and optimize.
Key job responsibilities
- Set the multi-year research direction for operations research across contact-center demand prediction, workforce scheduling, and network optimization.
- Design and deliver novel algorithms in combinatorial optimization (large-scale scheduling, resource allocation, integer/constraint programming) and queueing theory (contact-center modeling, staffing under stochastic arrivals), alongside stochastic modeling and time-series forecasting, that advance the state of the art while solving real operational problems.
- Own end-to-end scientific solutions — from problem formulation and prototyping to production deployment — ensuring robustness, explainability, and seamless integration with existing systems.
- Design rigorous experiments and evaluation methodology to validate hypotheses and quantify business impact; establish scientific-excellence mechanisms (metrics, benchmarks, peer review) that the broader science team adopts.
- Partner with engineering, product, and operations teams to define data and logging requirements, get them prioritized on roadmaps, and translate scientific capabilities into measurable business outcomes.
- Influence senior leadership through written papers and deep-dives, framing complex algorithmic trade-offs in clear business terms.
- Mentor and raise the bar for applied and research scientists across the org while maintaining significant hands-on technical contribution.
- Represent the team's science externally where appropriate (publications, patents, top-tier venues such as INFORMS, NeurIPS, ICML).
A day in the life
Your day blends hands-on science with technical leadership. You might spend the morning deep in data and models — prototyping a new combinatorial-optimization formulation for workforce scheduling or a queueing model for staffing under stochastic arrivals against production infrastructure — and the afternoon guiding fellow scientists through a hard optimization or stochastic-modeling problem, reviewing an experiment design, or aligning engineering partners on the data architecture needed to unlock the next capability. You'll drive technical discussions with the team and key stakeholders, and periodically write and present papers that shape the business and engineering roadmap.
BASIC QUALIFICATIONS
- 10+ years of tech industry or equivalent experience
- PhD in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field
- Experience working effectively with science, data processing, and software engineering teams
PREFERRED QUALIFICATIONS
- PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or experience in at least one of the related science disciplines (optimization - LP, MIP, statistics, machine learning, process control, combinatorial optimization)
- Experience in leading large-scale, technical or engineering programs with a proven record of thought leadership, business case development, realizing customer benefits, and successful program completion
- Experience scripting in modern programming languages, or experience with training and deploying machine learning systems to solve large-scale optimizations
- Patents or publications at top-tier peer-reviewed conferences or journals.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
COMPENSATION
- The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, NY, New York - 208,300.00 - 281,800.00 USD annually
DESCRIPTION
Do you want to define the scientific direction for how a global contact-center network forecasts demand, schedules its workforce, and optimizes operations in real time? The Eliza team within Amazon Connect (FCS) is looking for a Principal Research Scientist with a deep operations research specialization to set the research agenda in operations science — combinatorial optimization, queueing theory, stochastic modeling, and forecasting — and to translate that research into production systems that serve millions of customer interactions.
As a Principal Research Scientist, you will be the senior technical voice for operations research across the org. You will identify the highest-leverage scientific problems, architect novel solutions, and drive them from research through production deployment. You will not sit apart from the work — you will remain deeply hands-on with data, models, and systems while raising the scientific bar for scientists and engineers around you. This is an individual-contributor Principal role: your influence comes from technical depth, invention, and the ability to move business and engineering roadmaps through scientific rigor.
You will operate at the intersection of demand forecasting, workforce scheduling, and network optimization — applying combinatorial optimization to large-scale scheduling and resource-allocation problems and queueing theory to model contact-center dynamics under uncertainty, non-stationarity, and competing operational constraints at Internet scale — turning that reasoning into systems that continuously sense, predict, and optimize.
Key job responsibilities
- Set the multi-year research direction for operations research across contact-center demand prediction, workforce scheduling, and network optimization.
- Design and deliver novel algorithms in combinatorial optimization (large-scale scheduling, resource allocation, integer/constraint programming) and queueing theory (contact-center modeling, staffing under stochastic arrivals), alongside stochastic modeling and time-series forecasting, that advance the state of the art while solving real operational problems.
- Own end-to-end scientific solutions — from problem formulation and prototyping to production deployment — ensuring robustness, explainability, and seamless integration with existing systems.
- Design rigorous experiments and evaluation methodology to validate hypotheses and quantify business impact; establish scientific-excellence mechanisms (metrics, benchmarks, peer review) that the broader science team adopts.
- Partner with engineering, product, and operations teams to define data and logging requirements, get them prioritized on roadmaps, and translate scientific capabilities into measurable business outcomes.
- Influence senior leadership through written papers and deep-dives, framing complex algorithmic trade-offs in clear business terms.
- Mentor and raise the bar for applied and research scientists across the org while maintaining significant hands-on technical contribution.
- Represent the team's science externally where appropriate (publications, patents, top-tier venues such as INFORMS, NeurIPS, ICML).
A day in the life
Your day blends hands-on science with technical leadership. You might spend the morning deep in data and models — prototyping a new combinatorial-optimization formulation for workforce scheduling or a queueing model for staffing under stochastic arrivals against production infrastructure — and the afternoon guiding fellow scientists through a hard optimization or stochastic-modeling problem, reviewing an experiment design, or aligning engineering partners on the data architecture needed to unlock the next capability. You'll drive technical discussions with the team and key stakeholders, and periodically write and present papers that shape the business and engineering roadmap.
BASIC QUALIFICATIONS
- 10+ years of tech industry or equivalent experience
- PhD in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field
- Experience working effectively with science, data processing, and software engineering teams
PREFERRED QUALIFICATIONS
- PhD in operations research, applied mathematics, theoretical computer science, or equivalent, or experience in at least one of the related science disciplines (optimization - LP, MIP, statistics, machine learning, process control, combinatorial optimization)
- Experience in leading large-scale, technical or engineering programs with a proven record of thought leadership, business case development, realizing customer benefits, and successful program completion
- Experience scripting in modern programming languages, or experience with training and deploying machine learning systems to solve large-scale optimizations
- Patents or publications at top-tier peer-reviewed conferences or journals.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
COMPENSATION
- The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, NY, New York - 208,300.00 - 281,800.00 USD annually
Principal Research Scientist Job Roles in New York
See all 39+ Principal Research Scientist Jobs in New York
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Search Principal Research Scientist Jobs in New YorkPrincipal Research Scientist Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for principal research scientists in New York?
IBM Research in Yorktown Heights, Memorial Sloan Kettering Cancer Center, Pfizer, Bristol Myers Squibb, and Regeneron are among the most active sponsors for principal research scientist roles in New York. Academic medical centers such as Weill Cornell Medicine and Mount Sinai also file sponsorship petitions regularly for senior research positions across computational biology, oncology, and translational science.
Which visa types realistically fit principal research scientist roles in New York?
Principal research scientist roles typically qualify as specialty occupations requiring a directly related advanced degree, making H-1B visa the most common path. Candidates with an advanced degree from a U.S. institution may access the H-1B advanced degree exemption. EB-2 and EB-3 employment-based green cards are common long-term routes, with EB-2 NIW available for researchers whose work serves the U.S. national interest. J-1 visa is an option through designated exchange sponsor organizations, particularly for postdoctoral researchers.
Which cities in New York have the most principal research scientist sponsorship jobs?
New York City, particularly Manhattan and its surrounding boroughs, accounts for the largest share of principal research scientist sponsorship activity, driven by pharmaceutical companies, academic hospitals, and AI research labs. Westchester County, home to IBM Research's Yorktown Heights campus, is a secondary hub. Long Island's North Shore, anchored by Cold Spring Harbor Laboratory and Stony Brook University, is a notable cluster for life sciences and genomics research.
How to find principal research scientist visa sponsorship jobs in New York?
Migrate Mate lists principal research scientist roles in New York specifically from employers with verified visa sponsorship history, so you can focus your search on companies already familiar with the sponsorship process. Filtering by New York and this role category surfaces active openings at research institutions, biopharma companies, and technology labs across the state without having to manually vet each employer's willingness to sponsor.
Are there state-specific factors that affect principal research scientist hiring and sponsorship in New York?
New York's concentration of NIH-funded research institutions, top-ranked medical schools, and major pharmaceutical headquarters creates strong employer demand for sponsored senior scientists. The state's density of H-1B-active employers in life sciences and artificial intelligence means many hiring managers at New York institutions are already experienced with the sponsorship process. Candidates with a Ph.D. and a publication record in fields like computational biology, neuroscience, or machine learning are particularly well-positioned given local employer needs.
What is the prevailing wage for sponsored principal research scientist jobs in New York?
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.