Science & Research H-1B1 Singapore Sponsorship Jobs in New York
Science and research H-1B1 Singapore sponsorship jobs in New York are concentrated at institutions like Memorial Sloan Kettering, Columbia University, and major pharmaceutical firms in the Hudson Valley corridor. Singapore nationals with degrees in life sciences, chemistry, or biomedical engineering will find New York among the most active states for specialty occupation research hiring.
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Get Access To All JobsAbout Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
We're hiring a Product Operations Manager — Feedback Loops to own and continuously improve how customer signal flows into product and research decisions at Anthropic. This is a horizontal, org-wide role — you won't be embedded in a single product team, you'll build the shared operating system for voice of the customer that every product team, every surface, and every GTM motion plugs into. Feedback at Anthropic is uniquely high-leverage. We're building on frontier models that evolve constantly, serving customers from individual developers to the largest enterprises, across multiple surfaces (API, claude.ai, Claude Code). Customer signal arrives from everywhere — field conversations, support interactions, early access programs, in-product telemetry — and the opportunity is to make that signal a first-class, structured input to every product and research decision. This role will build the system that makes customer voice as easy to act on as any other data source. You treat feedback loops as a product. You're obsessed with making it effortless for the field to share what they're hearing and for product teams to know what matters most. You build AI-enabled systems that do the first pass so humans can focus on judgment, not triage. You think like a product manager, not a process administrator. Your work will directly impact how fast Anthropic learns from its customers and how reliably that learning shapes what we build next.
Key Responsibilities
You'll own the operating system for customer feedback across all of Anthropic — one shared platform, not a collection of per-team processes. Working horizontally across every Product team, Research PM, GTM, Customer Success, and Support, you'll establish the intake, synthesis, and routing infrastructure that makes voice of the customer a first-class input to every roadmap. You'll drive adoption through influence, making it so obviously useful that teams pull from it rather than get pushed to it.
Feedback Intake & System of Record
- Own the single, org-wide pipeline that captures customer feedback from every channel — field teams, support, early access programs, in-product signals — into one structured system of record that serves every product surface.
- Build intake workflows that meet teams where they already work (Slack, Gong, CRM) without creating a documentation tax. Obsess over the submitter experience so that sharing feedback is faster than not sharing it.
AI-Enabled Synthesis & Triage
- Build Claude-powered pipelines that enrich, tag, cluster, and summarize unstructured feedback into trackable issues — doing the first-pass work so humans focus on verification and judgment.
- Design the human-in-the-loop model: Claude proposes, PMs and field teams correct, and the system learns from those corrections over time.
- Partner with Engineering and Research on tooling strategy, evals, and the closed-loop data that makes synthesis quality measurably improve.
Routing & Closing the Loop
- Establish clear routing so the right feedback reaches the right product or research owner at the right time — including the path from product signal back into model training priorities.
- Build the visibility layer that gives GTM and Support a clear line of sight from customer input to roadmap outcome, so they can close the loop with customers confidently and in real time.
Voice of the Customer Programs
- Partner deeply with GTM, Customer Success, and Sales to design and run structured voice of the customer programs — customer advisory boards, early access programs, design partner cohorts — that generate high-signal feedback by design.
- Define what "high-signal" means: feedback tied to specific use cases, blocker severity, revenue context, and customer segments so product teams can make confident tradeoffs.
Continuous Improvement
- Define and track success metrics for feedback loop health — time-to-triage, signal quality, roadmap influence, field satisfaction — and use them to identify bottlenecks.
- Run regular retros with Product and GTM partners and feed learnings back into process and tooling improvements. Scale what works through documentation and enablement.
You May Be a Good Fit If You
- Have 7+ years in product operations, customer insights, voice of the customer programs, or related roles in fast-paced tech companies.
- Have personally shipped AI-enabled processes and systems — you've written the prompts, built the evals, and iterated on production LLM workflows yourself. You can talk about model behavior with specificity, not just direct others to build.
- Have owned a customer feedback program end-to-end — intake, synthesis, routing, and closing the loop — that product teams actually used to make decisions. The customer mix can be enterprise, PLG, design partner, or dev community; what matters is that you designed it and ran it.
- Have operated at earlier-stage and scaling companies (Series B-D or equivalent) where you built things that didn't exist yet, shipped v1s in weeks not quarters, and iterated in public.
- Have operated in horizontal, cross-org roles before — you know how to build shared infrastructure that many teams depend on, drive adoption through influence rather than mandate, and earn trust across functions that don't report to you.
- Are comfortable with ambiguity and can create structure where none exists — you've built the v1 of a system and iterated it into something teams rely on.
- Are service-oriented and obsessed with making it easy for others to do great work.
Strong Candidates May Also Have Experience With
- Building AI-native workflows end-to-end — prompt design, evals, closed-loop improvement — and pushing the boundaries of what automation can own.
- Product Management, Customer Success Operations, or Research Operations.
- Feedback tooling ecosystems (Productboard, Dovetail, or homegrown equivalents) and the tradeoffs between buy vs. build.
- Treating process as a product with users, metrics, and continuous iteration.
- Track record of building and scaling operations programs from zero to one.
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$260,000—$325,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
We're hiring a Product Operations Manager — Feedback Loops to own and continuously improve how customer signal flows into product and research decisions at Anthropic. This is a horizontal, org-wide role — you won't be embedded in a single product team, you'll build the shared operating system for voice of the customer that every product team, every surface, and every GTM motion plugs into. Feedback at Anthropic is uniquely high-leverage. We're building on frontier models that evolve constantly, serving customers from individual developers to the largest enterprises, across multiple surfaces (API, claude.ai, Claude Code). Customer signal arrives from everywhere — field conversations, support interactions, early access programs, in-product telemetry — and the opportunity is to make that signal a first-class, structured input to every product and research decision. This role will build the system that makes customer voice as easy to act on as any other data source. You treat feedback loops as a product. You're obsessed with making it effortless for the field to share what they're hearing and for product teams to know what matters most. You build AI-enabled systems that do the first pass so humans can focus on judgment, not triage. You think like a product manager, not a process administrator. Your work will directly impact how fast Anthropic learns from its customers and how reliably that learning shapes what we build next.
Key Responsibilities
You'll own the operating system for customer feedback across all of Anthropic — one shared platform, not a collection of per-team processes. Working horizontally across every Product team, Research PM, GTM, Customer Success, and Support, you'll establish the intake, synthesis, and routing infrastructure that makes voice of the customer a first-class input to every roadmap. You'll drive adoption through influence, making it so obviously useful that teams pull from it rather than get pushed to it.
Feedback Intake & System of Record
- Own the single, org-wide pipeline that captures customer feedback from every channel — field teams, support, early access programs, in-product signals — into one structured system of record that serves every product surface.
- Build intake workflows that meet teams where they already work (Slack, Gong, CRM) without creating a documentation tax. Obsess over the submitter experience so that sharing feedback is faster than not sharing it.
AI-Enabled Synthesis & Triage
- Build Claude-powered pipelines that enrich, tag, cluster, and summarize unstructured feedback into trackable issues — doing the first-pass work so humans focus on verification and judgment.
- Design the human-in-the-loop model: Claude proposes, PMs and field teams correct, and the system learns from those corrections over time.
- Partner with Engineering and Research on tooling strategy, evals, and the closed-loop data that makes synthesis quality measurably improve.
Routing & Closing the Loop
- Establish clear routing so the right feedback reaches the right product or research owner at the right time — including the path from product signal back into model training priorities.
- Build the visibility layer that gives GTM and Support a clear line of sight from customer input to roadmap outcome, so they can close the loop with customers confidently and in real time.
Voice of the Customer Programs
- Partner deeply with GTM, Customer Success, and Sales to design and run structured voice of the customer programs — customer advisory boards, early access programs, design partner cohorts — that generate high-signal feedback by design.
- Define what "high-signal" means: feedback tied to specific use cases, blocker severity, revenue context, and customer segments so product teams can make confident tradeoffs.
Continuous Improvement
- Define and track success metrics for feedback loop health — time-to-triage, signal quality, roadmap influence, field satisfaction — and use them to identify bottlenecks.
- Run regular retros with Product and GTM partners and feed learnings back into process and tooling improvements. Scale what works through documentation and enablement.
You May Be a Good Fit If You
- Have 7+ years in product operations, customer insights, voice of the customer programs, or related roles in fast-paced tech companies.
- Have personally shipped AI-enabled processes and systems — you've written the prompts, built the evals, and iterated on production LLM workflows yourself. You can talk about model behavior with specificity, not just direct others to build.
- Have owned a customer feedback program end-to-end — intake, synthesis, routing, and closing the loop — that product teams actually used to make decisions. The customer mix can be enterprise, PLG, design partner, or dev community; what matters is that you designed it and ran it.
- Have operated at earlier-stage and scaling companies (Series B-D or equivalent) where you built things that didn't exist yet, shipped v1s in weeks not quarters, and iterated in public.
- Have operated in horizontal, cross-org roles before — you know how to build shared infrastructure that many teams depend on, drive adoption through influence rather than mandate, and earn trust across functions that don't report to you.
- Are comfortable with ambiguity and can create structure where none exists — you've built the v1 of a system and iterated it into something teams rely on.
- Are service-oriented and obsessed with making it easy for others to do great work.
Strong Candidates May Also Have Experience With
- Building AI-native workflows end-to-end — prompt design, evals, closed-loop improvement — and pushing the boundaries of what automation can own.
- Product Management, Customer Success Operations, or Research Operations.
- Feedback tooling ecosystems (Productboard, Dovetail, or homegrown equivalents) and the tradeoffs between buy vs. build.
- Treating process as a product with users, metrics, and continuous iteration.
- Track record of building and scaling operations programs from zero to one.
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$260,000—$325,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
H-1B1 Singapore Science & Research Job Roles in New York
See all 181+ Science & Research H-1B1 Singapore Jobs in New York
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Search Science & Research Jobs in New YorkScience & Research H-1B1 Singapore Sponsorship Jobs in New York: Frequently Asked Questions
Which science and research companies sponsor H-1B1 Singapore visas in New York?
Major sponsors include academic medical centers such as Memorial Sloan Kettering Cancer Center, Rockefeller University, and NYU Langone, alongside pharmaceutical and biotechnology firms concentrated in the Hudson Valley and Long Island biotech corridors. Large research-intensive corporations like Pfizer, which maintains significant research operations in New York, have consistent H-1B1 Singapore LCA filing histories verifiable through OFLC disclosure data.
Which cities in New York have the most science and research H-1B1 Singapore sponsorship jobs?
New York City accounts for the largest share, driven by its dense cluster of academic medical centers, university research departments, and private biotech firms in Manhattan, Brooklyn, and the Bronx. Pearl River and Tarrytown in the Hudson Valley host pharmaceutical research campuses. Long Island, particularly around Stony Brook and Cold Spring Harbor Laboratory, is also a consistent source of research sponsorship opportunities for Singapore nationals.
What types of science and research roles typically qualify for H-1B1 Singapore sponsorship?
Roles that qualify are those meeting the specialty occupation standard, requiring at least a bachelor's degree in a directly related scientific field. Common qualifying titles include research scientist, computational biologist, biochemist, clinical research associate, data scientist in a research context, and laboratory scientist. Positions in basic research, translational medicine, and drug discovery at New York institutions regularly appear in H-1B1 Singapore LCA filings reviewed through O*NET occupation classifications.
How do I find science and research H-1B1 Singapore sponsorship jobs in New York?
Migrate Mate filters job listings specifically for H-1B1 Singapore sponsorship in New York, letting you search by science and research roles without sifting through employers with no relevant filing history. Because Migrate Mate surfaces DOL Labor Condition Application data by employer and occupation, you can see which New York research institutions and biotech firms have actively sponsored Singapore nationals for specialty occupation roles before you apply.
Are there any New York-specific or industry-specific considerations for H-1B1 Singapore sponsorship in science and research?
New York research employers filing an LCA must post the notice at the specific worksite, which matters if you will be working across multiple hospital or campus locations. Academic and nonprofit research institutions are often cap-exempt for H-1B visa purposes but must still comply with all H-1B1 Singapore prevailing wage requirements set by DOL. Singapore nationals benefit from the H-1B visa1 category having no annual lottery, though each employer must independently demonstrate the role meets specialty occupation standards as assessed by USCIS.
What is the prevailing wage for H-1B1 Singapore science & research 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.