Research Engineer Visa Sponsorship Jobs in New Jersey
New Jersey's research engineer job market is anchored by pharmaceutical giants like Johnson & Johnson and Merck in the Route 1 corridor, major tech labs along the I-287 corridor, and proximity to Princeton University's research ecosystem. Cities including New Brunswick, Princeton, and Parsippany concentrate the most sponsorship activity for research engineer roles in the state.
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Job Description:
We believe in bold ideas, diverse perspectives, and the drive to transform knowledge into impact. Here, your curiosity fuels progress, your voice shapes innovation, and your ambition helps redefine what’s possible within science and learning. We are a culture that obsesses over impact, challenges, and drives what’s next to power infinite possibilities for our customers, colleagues and society at large.
About the Role:
Group Vice President (GVP) and General Manager (GM), Applied Research Intelligence
AI & Data Analytics Business Unit
Position Overview
Applied Research Intelligence is positioned to become a category-defining business that connects the world’s scientific knowledge with the decisions it can inform. As Group Vice President and General Manager, Applied Research Intelligence, you will be the commercial owner and business builder at the center of this opportunity, leading a high-growth business focused on enterprise R&D intelligence.
You will report to the Chief AI & Data Analytics Officer and lead a high-performing commercial organization focused on turning proprietary scientific content, data assets, and AI-enabled capabilities into scalable solutions for enterprise customers across pharmaceuticals, biotechnology, engineering, agriculture, and adjacent innovation-driven sectors.
This is a build mandate: you will have full profit-and-loss ownership, the authority to shape the commercial model, and the opportunity to scale a business that sits at the intersection of scientific expertise, proprietary data, and applied AI.
You will be the visible, commercially accountable leader customers, cloud and technology partners, and strategic co-development partners engage with when they want to understand the business’s direction, ambition, and ability to win in a rapidly evolving market.
Key Responsibilities
P& L Ownership
- Hold full profit-and-loss accountability for a consolidated Applied Research Intelligence business of approximately $100M+ in revenue, spanning content knowledge feeds, database solutions, commercial licensing and partnerships, and the newly launched Applied Research Intelligence platform.
- Own the revenue forecast, financial performance, and operating rhythm for all four business lines, using commercial levers to manage variance, improve predictability, and close gaps against plan.
- Lead the shift toward higher-quality recurring revenue, increasing the recurring mix from 80% through platform subscriptions, data-feed contracts, database SaaS migration, and recurring partnership arrangements.
- Own the operating expense budget and multi-year investment plan across technology, product, sales, marketing, and operations, ensuring capital is deployed against clear milestones and measurable value creation.
- Own pricing strategy and models across all four business lines.
- Govern the business's dependency on shared AI & Data Analytics platform infrastructure, including product, engineering, and data science capabilities that sit outside this role's direct organization, ensuring commercial commitments and revenue targets are matched by platform delivery capacity, and escalating capacity or roadmap misalignment before it puts revenue commitments at risk.
- Exercise strong influence over the shared product/engineering roadmap, ensuring platform delivery capacity is matched to commercial commitments.
Commercial Ownership
- Define the market and commercial strategy, customer engagement model, pricing approach, and platform readiness required to scale the business: deciding where to compete, building the commercial infrastructure to win, and converting data, content, and AI-enabled products into durable revenue.
- Build a commercial team and culture suited to a business in transition: hire and develop leaders who are entrepreneurial, customer-led, disciplined on execution, and comfortable moving from legacy content models toward scalable intelligence platforms.
Corporate R& D Go-to-Market
- Lead enterprise go-to-market across the three target buyer archetypes: top-tier pharma AI and data science teams; corporate R&D; and librarians and knowledge managers.
- Drive demand generation and account-based marketing programs with a clear pipeline handoff rhythm that connects marketing investment directly to commercial outcomes.
- Develop a repeatable commercial playbook for life sciences and healthcare that can be extended into other enterprise R&D verticals.
Strategic Partnerships & Competitive Positioning
- Own the commercial relationship and deal structure for strategic partnerships across product extensions, vertical AI applications, commercial licensing, and partner-led distribution models.
- Build integration and referral partnerships across clinical decision support, pre-clinical drug discovery, personalized medicine, education, and certification use cases.
- Own and evolve the IP and content-licensing strategy, including structuring multi-party licensing agreements and optimizing licensing yield across content and data assets.
Market Intelligence & Demand Signal
- Serve as the primary source of enterprise R&D market intelligence for the business: translating customer conversations, partner input, evidence from the market, and competitive observations into actionable demand signals for product and data science leaders.
- Identify which use cases are active in customer conversations, which evidence and content-depth questions enterprise buyers are asking, and which competitive capabilities are shaping buying decisions.
- Contribute to vertical selection and use-case prioritization by providing clear commercial input on market attractiveness, buyer urgency, differentiation, and invest-or-do-not-invest decisions.
- Maintain awareness of adjacent customer segments and cross-sell opportunities where enterprise R&D, knowledge management, and audience-based buyer needs overlap, including adjacent data categories such as clinical/regulatory and other domain data relevant to enterprise R&D buyers.
Required Experience & Qualifications
- Experience leading commercial or product organizations within scientific, patent/IP, or regulated R&D data ecosystems (e.g., pharma, biotech, patent analytics)
- Proven track record as a commercial GM with full P&L ownership in a data, AI, or technology business.
- Experience building, scaling, and commercializing complex data, AI, knowledge/database, or technology products for enterprise buyers, including managing investment decisions against clear milestones and performance indicators.
- Deep enterprise go-to-market experience in corporate R&D markets such as pharmaceuticals, biotechnology, engineering, agriculture, or adjacent sectors; demonstrated ability to navigate technical buying processes, build trust with AI and data science teams, and close multi-year enterprise contracts.
- Strong commercial fluency in data product economics, including licensing models, subscription architectures, usage-based pricing, API monetization, and the shift from transactional revenue toward recurring, subscription-based income.
- Demonstrated ability to build and lead high-performing commercial organizations through a period of significant strategic transformation while maintaining performance in existing revenue lines.
- Track record of building strategic partnerships that generate near-term commercial return.
- The commercial credibility and technical fluency to represent the business externally to enterprise buyers, cloud and technology partners, investment committees, and the board.
- A builder’s orientation: energized by creating new markets, shaping teams and operating models, testing commercial hypotheses, and scaling from early traction to repeatable growth.
- First-hand experience inside a corporate R&D, IP, or scientific operations function is a strong plus.
- Advanced degree (MBA, PhD, or equivalent) in a scientific or business discipline preferred.
Success Metrics
- Deliver 12% year-over-year consolidated revenue growth while continuing to expand recurring revenue by at least 10%.
- Shift the revenue mix so platform subscriptions, database API/SaaS offerings, and recurring licensing arrangements exceed one-time training revenue.
We power infinite possibilities.
For more than 200 years, we've transformed knowledge into discoveries that shape the world. Today, our global team of innovators, creators, and experts is driving what's next in science, education, and publishing—creating impact that reaches everywhere.
We're not just observers of progress. We're the ones accelerating scientific breakthroughs, advancing learning, and sparking innovation that redefines entire fields and improves lives.
Here, your talent matters. Your ideas have room to grow. And your work creates breakthroughs that can change everything.
Wiley is an equal opportunity/affirmative action employer. We evaluate all qualified applicants and treat all qualified applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, protected veteran status, genetic information, or based on any individual's status in any group or class protected by applicable federal, state or local laws. Wiley is also committed to providing reasonable accommodation to applicants and employees with disabilities. Applicants who require accommodation to participate in the job application process may contact tasupport@wiley.com for assistance.
We are proud that our workplace promotes continual learning and internal mobility. Our values support courageous teammates, needle movers, and learning champions all while striving to support the health and well-being of all employees. We offer meeting-free Friday afternoons allowing more time for heads down work and professional development, and through a robust body of employee programming we facilitate a wide range of opportunities to foster community, learn, and grow.
We are committed to fair, transparent pay, and we strive to provide competitive compensation in addition to a comprehensive benefits package. The range below represents Wiley's good faith and reasonable estimate of the base pay for this role at the time of posting roles in the United Kingdom, Canada, USA, Austria, Czechia, Denmark, France, Greece, Italy, Netherlands, Romania, or Spain. It is anticipated that most qualified candidates will fall within the range, however the ultimate salary offered for this role may be higher or lower and will be set based on a variety of non-discriminatory factors, including but not limited to, geographic location, skills, and competencies.
When applying, please attach your resume/CV to be considered.
Salary Range:
218,900.00 USD to 328,566.66 USD
Research Engineer Job Roles in New Jersey
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Search Research Engineer Jobs in New JerseyResearch Engineer Jobs in New Jersey: Frequently Asked Questions
Which companies sponsor visas for research engineers in New Jersey?
Johnson & Johnson, Merck, Sanofi, and Siemens are among the most active sponsors of research engineer roles in New Jersey, particularly in pharmaceutical R&D and advanced engineering. AT&T Labs in Bedminster and various biotech firms along the Route 1 corridor have also filed H-1B visa Labor Condition Applications for research engineering positions in recent years.
Which visa types are most common for research engineer roles in New Jersey?
The H-1B is the most common visa category for research engineers in New Jersey, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in engineering, computer science, or a related technical field. Candidates with exceptional publication records or patents may also qualify for the O-1A. Those on F-1 OPT in STEM fields can work for up to three years before needing H-1B sponsorship.
Which cities in New Jersey have the most research engineer sponsorship jobs?
Princeton and New Brunswick lead in research engineer sponsorship activity, driven by proximity to Princeton University and the pharmaceutical corridor along Route 1. Parsippany, Bedminster, and Murray Hill also see consistent sponsorship, particularly from large corporate research labs. Newark is growing as a secondary hub, supported by university research programs at Rutgers and NJIT.
How to find research engineer visa sponsorship jobs in New Jersey?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to search for research engineer roles in New Jersey without sifting through positions that don't offer sponsorship. You can narrow results by location and job title to focus on New Jersey's pharmaceutical, tech, and engineering research sectors, where sponsorship activity is most concentrated.
Are there state-specific or role-specific factors that affect research engineer sponsorship in New Jersey?
New Jersey's concentration of pharmaceutical and life sciences employers means many research engineer openings are tied to specialized R&D functions, which can strengthen a specialty occupation determination for H-1B purposes. The state also benefits from strong university pipelines through Princeton, Rutgers, and Stevens Institute of Technology, where employers actively recruit international candidates and have established sponsorship processes in place.
What is the prevailing wage for sponsored research engineer jobs in New Jersey?
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.