Scientist Visa Sponsorship Jobs in New York
New York's scientist job market spans pharmaceutical research corridors in Manhattan, biotech clusters on Long Island, and academic medical centers affiliated with institutions like Columbia, Cornell, and Rockefeller University. Major employers including Pfizer, Memorial Sloan Kettering, and Cold Spring Harbor Laboratory have established histories of sponsoring work visas for qualified research scientists.
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Get Access To All JobsAbout Faire
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.
We're looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About the Role
As a Staff Applied Scientist on the Discovery team, you'll own how Faire measures and optimizes the long-term value of a discovery impression — one of the highest-leverage open problems on our marketplace. Our rankers today optimize for order conversion, helping retailers find brands and products they love. But we know our ranking algorithms can do more: helping retailers find not just products they love, but brands they can build long-lasting, successful partnerships with.
Reordering is one clear signal of this — successful brand-retailer relationships compound into substantial reorder volume over time — but not every discovery order evolves into a lasting partnership. Identifying the ones that will compound, and helping them grow, matters enormously for our community.
This is a rare opportunity to define a measurement problem from first principles. You'll build the LTV framework, design the experiments that validate it, and turn the result into a shared signal that all discovery algorithms can act on.
- Own how we measure and optimize the long-term value of a discovery impression — how it contributes to the discovery of new brands retailers might love, and how it strengthens existing promising relationships so they compound.
- Create the initial LTV framework: form and prioritize hypotheses about what drives long-term relationship value and the key short- vs. long-term tradeoffs, with assumptions made explicit and testable, and lay out the experimentation roadmap to validate and refine it.
- Lead the implementation of v0 of the LTV model into a long-running ranking experiment, setting north star metrics as well as guardrails to maximize organizational learning, with a defined readout cadence and course-correction plan.
- Deliver the long-term surrogate metric — a near-term readout predictive of long-term value — accounting for confounding factors and inherent uncertainties in measurement and marketplace dynamics.
- Own the LTV model tech stack and operating standards, continuously improving the capabilities and accuracy of the model as it becomes consumable across search, reorder, and ads.
You're a Great Fit If You Have…
- 5+ years applying ML and statistical modeling to real business problems, shipping to production.
- Deep causal inference expertise — quasi-experimental methods, rigorous confounder control, and healthy skepticism of analytical results.
- Strong experimentation design skills, especially long-horizon experiments — surrogate/proxy metrics and variance reduction for sparse, delayed outcomes.
- Baseline knowledge of search and recommendation systems on e-commerce or marketplace platforms.
- Strong statistical analysis and data engineering skills — SQL/ETL and data transformation at scale.
- An excitement and willingness to learn new tools and techniques.
- Excellent communication skills and the ability to work in a highly cross-functional team.
Bonus Points For…
- PhD in CS, Stats, Economics, OR, or a related STEM field.
- LTV / lifetime-value optimization on a two-sided marketplace, e-commerce platform, or other recommendation systems.
- Deep learning, machine learning, or learning-to-rank techniques.
Salary Range
San Francisco & New York: the pay range for this role is $246,500 to $339,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
Why you'll love working at Faire
- Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
- Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
- Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
- Real rewards: Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
- Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.
Faire was founded in 2017 by a team of early product and engineering leads from Square. We're backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog.
Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form.
Privacy
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire's Privacy Notice.
About Faire
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.
We're looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About the Role
As a Staff Applied Scientist on the Discovery team, you'll own how Faire measures and optimizes the long-term value of a discovery impression — one of the highest-leverage open problems on our marketplace. Our rankers today optimize for order conversion, helping retailers find brands and products they love. But we know our ranking algorithms can do more: helping retailers find not just products they love, but brands they can build long-lasting, successful partnerships with.
Reordering is one clear signal of this — successful brand-retailer relationships compound into substantial reorder volume over time — but not every discovery order evolves into a lasting partnership. Identifying the ones that will compound, and helping them grow, matters enormously for our community.
This is a rare opportunity to define a measurement problem from first principles. You'll build the LTV framework, design the experiments that validate it, and turn the result into a shared signal that all discovery algorithms can act on.
- Own how we measure and optimize the long-term value of a discovery impression — how it contributes to the discovery of new brands retailers might love, and how it strengthens existing promising relationships so they compound.
- Create the initial LTV framework: form and prioritize hypotheses about what drives long-term relationship value and the key short- vs. long-term tradeoffs, with assumptions made explicit and testable, and lay out the experimentation roadmap to validate and refine it.
- Lead the implementation of v0 of the LTV model into a long-running ranking experiment, setting north star metrics as well as guardrails to maximize organizational learning, with a defined readout cadence and course-correction plan.
- Deliver the long-term surrogate metric — a near-term readout predictive of long-term value — accounting for confounding factors and inherent uncertainties in measurement and marketplace dynamics.
- Own the LTV model tech stack and operating standards, continuously improving the capabilities and accuracy of the model as it becomes consumable across search, reorder, and ads.
You're a Great Fit If You Have…
- 5+ years applying ML and statistical modeling to real business problems, shipping to production.
- Deep causal inference expertise — quasi-experimental methods, rigorous confounder control, and healthy skepticism of analytical results.
- Strong experimentation design skills, especially long-horizon experiments — surrogate/proxy metrics and variance reduction for sparse, delayed outcomes.
- Baseline knowledge of search and recommendation systems on e-commerce or marketplace platforms.
- Strong statistical analysis and data engineering skills — SQL/ETL and data transformation at scale.
- An excitement and willingness to learn new tools and techniques.
- Excellent communication skills and the ability to work in a highly cross-functional team.
Bonus Points For…
- PhD in CS, Stats, Economics, OR, or a related STEM field.
- LTV / lifetime-value optimization on a two-sided marketplace, e-commerce platform, or other recommendation systems.
- Deep learning, machine learning, or learning-to-rank techniques.
Salary Range
San Francisco & New York: the pay range for this role is $246,500 to $339,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.
Why you'll love working at Faire
- Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
- Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
- Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
- Real rewards: Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
- Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.
Faire was founded in 2017 by a team of early product and engineering leads from Square. We're backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog.
Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form.
Privacy
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire's Privacy Notice.
Scientist Job Roles in New York
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Search Scientist Jobs in New YorkScientist Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for scientists in New York?
Pharmaceutical and biotech employers are the most active sponsors for scientist roles in New York. Companies such as Pfizer, Bristol Myers Squibb, and Regeneron, alongside academic medical centers like Memorial Sloan Kettering Cancer Center and NYU Langone Health, regularly file H-1B visa petitions for research scientists. National laboratories and environmental consulting firms operating in the state also have documented sponsorship histories.
Which visa types are most common for scientist roles in New York?
The H-1B is the most common visa category for scientists in New York, as research and laboratory roles typically qualify as specialty occupations requiring a relevant bachelor's degree or higher. Scientists at universities or affiliated research institutes may also encounter J-1 visa exchange visitor visas for postdoctoral positions. Those with exceptional research records may qualify for the O-1A or pursue employer-sponsored permanent residence through the EB-1B or EB-2 NIW pathways.
Which cities in New York have the most scientist sponsorship jobs?
New York City concentrates the greatest volume of sponsored scientist positions, particularly in Manhattan's pharmaceutical corridor and the medical research institutions of the Upper East Side. Long Island is a secondary hub, anchored by Cold Spring Harbor Laboratory and Stony Brook University's research programs. Albany and Buffalo host state agency research positions and university-affiliated science roles that also carry sponsorship potential.
How to find scientist visa sponsorship jobs in New York?
Migrate Mate is built specifically for international job seekers and filters scientist roles in New York by employers with active visa sponsorship histories, saving significant research time. Because sponsorship is not always disclosed in standard job postings, using a platform like Migrate Mate that surfaces H-1B filing data gives you a meaningful advantage when targeting pharmaceutical, biotech, and academic research employers across the state.
Are there state-specific considerations for scientists seeking sponsorship in New York?
New York's prevailing wage requirements under Department of Labor rules apply to H-1B petitions filed for positions in the state, and wages are benchmarked to the specific metropolitan area where you will work, so a role in Manhattan is assessed against New York City wage data rather than a statewide average. The state's dense concentration of NIH-funded research institutions also means that many scientist positions are tied to grant cycles, which can affect the timing and duration of sponsorship offers.
What is the prevailing wage for sponsored 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.