Green Card Quantitative Jobs
Quantitative roles in finance, tech, and data science are among the most actively PERM-sponsored positions in the U.S. market. Employers filing EB-2 and EB-3 petitions for quant analysts, researchers, and modelers follow a defined labor certification process before sponsorship can begin. Understanding where you fit in that pipeline shortens your path to a green card.
Find Green Card Quantitative JobsOverview
Showing 5 of 1,772+ Quantitative jobs
See all 1,772+ Quantitative Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Quantitative roles.
Get Access To All JobsINTRODUCTION
At Eisai, satisfying unmet medical needs and increasing the benefits healthcare provides to patients, their families, and caregivers is Eisai’s human health care (hhc) mission. We’re a growing pharmaceutical company that is breaking through in neurology and oncology, with a strong emphasis on research and development. Our history includes the development of many innovative medicines, notably the discovery of the world's most widely-used treatment for Alzheimer’s disease. As we continue to expand, we are seeking highly-motivated individuals who want to work in a fast-paced environment and make a difference. If this is your profile, we want to hear from you.
ROLE AND RESPONSIBILITIES
The Director of Quantitative Systems Pharmacology (QSP) will lead the development and implementation of mechanistic knowledge of biology integrated into mathematical models that support drug discovery and clinical development. The Director of QSP will provide scientific leadership, define QSP strategies, and collaborate across Eisai’s Deep Human Biology Learning (DHBL) project teams to translate existing knowledge and data into actionable QSP models. These models will provide functional understanding of complex nonlinear pathophysiological systems and their interactions, will allow scientists to explore system dynamics and biological hypotheses, will yield insight into responses to different pharmacological approaches to modulating biological systems, and will provide mechanistic insights to inform Eisai’s R&D decisions (for example FIH translation, dose selection, candidate selection, selection of target population, and combination strategies). This Director QSP position is essential for supporting the increasing expectations of team leaders and global regulators of applying QSP methodologies to continuously improve the conceptual and mechanistic understanding of the relations among drug exposure, efficacy, and safety.
Essential Functions:
- Develop, implement, and apply QSP models to understand diseases, their pathways, and their progressions. Evaluate DHBL drug candidates and treatment modalities to predict their effects and optimize therapeutic strategies (e.g., the selection of target tumor types and populations), and to support clinical introduction including first-in-human dose selection.
- Use and improve existing Neurology QSP Platforms to gain insights into the causal relationships between biological and drug-level responses, enhancing the understanding of drug-target interactions and disease mechanisms. Develop new QSP models and platforms as they are needed.
- Lead DHBL preclinical and early clinical QSP development strategy to support optimal dose selection with simulations based on mechanistic understanding to assess efficacy and safety.
- Advocate for model-informed drug discovery and development (MIDD) approaches. Provide scientific leadership, present research at scientific conferences, and integrate MIDD strategies into Eisai’s R&D programs to improve efficiency and decision-making.
- Foster collaboration across functional groups and promote the development of new modeling tools and methods. Advance the adoption of QSP capabilities to improve the predictive power of these tools to support the design and optimization of drug combinations.
- Manage the expectations/timelines of assigned M&S work for the relevant project teams.
- Use mathematical, computational, and statistical tools to analyze and interpret large, complex data sets to gain insights into the causal relationships between drug-target interactions and disease mechanisms.
- Provide scientific/strategic expertise across multiple therapeutic areas to support decision-making in the conversion of discovery to clinical through the design, development, and execution of quantitative mechanistic models to support the translational process.
REQUIREMENTS
- PhD, MD-PhD and/or PharmD in Bioengineering, Systems Biology, Applied Mathematics, Computational Biology, Pharmacometrics, Chemical Engineering, Pharmaceutical Sciences, or a related quantitative discipline.
- Deep knowledge of the principles and theoretical aspects of applied mathematical modeling, including numerical methods, ordinary differential equations (ODEs), partial differential equations (PDEs), parameter estimation/optimization, and how these tools can be applied in the development of complex biochemical models.
- Deep expertise in quantitative systems pharmacology (QSP), mechanistic modeling, systems biology, and translational science.
- Demonstrated experience applying QSP approaches to support drug discovery and/or clinical development programs with measurable program impact.
- Strong understanding of pharmacology, physiology, immunology, molecular biology, and disease mechanisms.
- Ability to learn quickly in new areas of biology and to use a solid foundation of quantitative skills to apply newly acquired knowledge to build mechanistically sound QSP models.
Eisai Salary Transparency Language:
The annual base salary range for the Director, Quantitative Systems Pharmacology is from $208,200-$273,200. Under current guidelines, this position is eligible to participate in Eisai Inc. Annual Incentive Plan & Eisai Inc. Long Term Incentive Plan. Final pay determinations will depend on various factors including but not limited to experience level, education, knowledge, and skills.
Employees are eligible to participate in Company employee benefit programs. For additional information on Company employee benefits programs, visit https://careers.eisai.com/us/en/compensation-and-benefits.
Certain other benefits may be available for this position, please discuss any questions with your recruiter.
Eisai is an equal opportunity employer and as such, is committed in policy and in practice to recruit, hire, train, and promote in all job qualifications without regard to race, color, religion, gender, age, national origin, citizenship status, marital status, sexual orientation, gender identity, disability or veteran status. Similarly, considering the need for reasonable accommodations, Eisai prohibits discrimination against persons because of disability, including disabled veterans.
Eisai Inc. participates in E-Verify. E-Verify is an Internet based system operated by the Department of Homeland Security in partnership with the Social Security Administration that allows participating employers to electronically verify the employment eligibility of all new hires in the United States. Please click on the following link for more information:
Right To Work
E-Verify Participation
INTRODUCTION
At Eisai, satisfying unmet medical needs and increasing the benefits healthcare provides to patients, their families, and caregivers is Eisai’s human health care (hhc) mission. We’re a growing pharmaceutical company that is breaking through in neurology and oncology, with a strong emphasis on research and development. Our history includes the development of many innovative medicines, notably the discovery of the world's most widely-used treatment for Alzheimer’s disease. As we continue to expand, we are seeking highly-motivated individuals who want to work in a fast-paced environment and make a difference. If this is your profile, we want to hear from you.
ROLE AND RESPONSIBILITIES
The Director of Quantitative Systems Pharmacology (QSP) will lead the development and implementation of mechanistic knowledge of biology integrated into mathematical models that support drug discovery and clinical development. The Director of QSP will provide scientific leadership, define QSP strategies, and collaborate across Eisai’s Deep Human Biology Learning (DHBL) project teams to translate existing knowledge and data into actionable QSP models. These models will provide functional understanding of complex nonlinear pathophysiological systems and their interactions, will allow scientists to explore system dynamics and biological hypotheses, will yield insight into responses to different pharmacological approaches to modulating biological systems, and will provide mechanistic insights to inform Eisai’s R&D decisions (for example FIH translation, dose selection, candidate selection, selection of target population, and combination strategies). This Director QSP position is essential for supporting the increasing expectations of team leaders and global regulators of applying QSP methodologies to continuously improve the conceptual and mechanistic understanding of the relations among drug exposure, efficacy, and safety.
Essential Functions:
- Develop, implement, and apply QSP models to understand diseases, their pathways, and their progressions. Evaluate DHBL drug candidates and treatment modalities to predict their effects and optimize therapeutic strategies (e.g., the selection of target tumor types and populations), and to support clinical introduction including first-in-human dose selection.
- Use and improve existing Neurology QSP Platforms to gain insights into the causal relationships between biological and drug-level responses, enhancing the understanding of drug-target interactions and disease mechanisms. Develop new QSP models and platforms as they are needed.
- Lead DHBL preclinical and early clinical QSP development strategy to support optimal dose selection with simulations based on mechanistic understanding to assess efficacy and safety.
- Advocate for model-informed drug discovery and development (MIDD) approaches. Provide scientific leadership, present research at scientific conferences, and integrate MIDD strategies into Eisai’s R&D programs to improve efficiency and decision-making.
- Foster collaboration across functional groups and promote the development of new modeling tools and methods. Advance the adoption of QSP capabilities to improve the predictive power of these tools to support the design and optimization of drug combinations.
- Manage the expectations/timelines of assigned M&S work for the relevant project teams.
- Use mathematical, computational, and statistical tools to analyze and interpret large, complex data sets to gain insights into the causal relationships between drug-target interactions and disease mechanisms.
- Provide scientific/strategic expertise across multiple therapeutic areas to support decision-making in the conversion of discovery to clinical through the design, development, and execution of quantitative mechanistic models to support the translational process.
REQUIREMENTS
- PhD, MD-PhD and/or PharmD in Bioengineering, Systems Biology, Applied Mathematics, Computational Biology, Pharmacometrics, Chemical Engineering, Pharmaceutical Sciences, or a related quantitative discipline.
- Deep knowledge of the principles and theoretical aspects of applied mathematical modeling, including numerical methods, ordinary differential equations (ODEs), partial differential equations (PDEs), parameter estimation/optimization, and how these tools can be applied in the development of complex biochemical models.
- Deep expertise in quantitative systems pharmacology (QSP), mechanistic modeling, systems biology, and translational science.
- Demonstrated experience applying QSP approaches to support drug discovery and/or clinical development programs with measurable program impact.
- Strong understanding of pharmacology, physiology, immunology, molecular biology, and disease mechanisms.
- Ability to learn quickly in new areas of biology and to use a solid foundation of quantitative skills to apply newly acquired knowledge to build mechanistically sound QSP models.
Eisai Salary Transparency Language:
The annual base salary range for the Director, Quantitative Systems Pharmacology is from $208,200-$273,200. Under current guidelines, this position is eligible to participate in Eisai Inc. Annual Incentive Plan & Eisai Inc. Long Term Incentive Plan. Final pay determinations will depend on various factors including but not limited to experience level, education, knowledge, and skills.
Employees are eligible to participate in Company employee benefit programs. For additional information on Company employee benefits programs, visit https://careers.eisai.com/us/en/compensation-and-benefits.
Certain other benefits may be available for this position, please discuss any questions with your recruiter.
Eisai is an equal opportunity employer and as such, is committed in policy and in practice to recruit, hire, train, and promote in all job qualifications without regard to race, color, religion, gender, age, national origin, citizenship status, marital status, sexual orientation, gender identity, disability or veteran status. Similarly, considering the need for reasonable accommodations, Eisai prohibits discrimination against persons because of disability, including disabled veterans.
Eisai Inc. participates in E-Verify. E-Verify is an Internet based system operated by the Department of Homeland Security in partnership with the Social Security Administration that allows participating employers to electronically verify the employment eligibility of all new hires in the United States. Please click on the following link for more information:
Right To Work
E-Verify Participation
See all 1,772+ Green Card Quantitative Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Green Card Quantitative Jobs.
Get Access To All JobsTips for Finding Green Card Sponsorship in Quantitative
Match your degree to the EB tier
EB-2 requires a master's or higher in a quantitative field like mathematics, statistics, or financial engineering. If you hold a bachelor's plus five years of progressive quant experience, document that progression carefully because USCIS scrutinizes the degree-equivalency claim on I-140 petitions.
Target employers with active PERM history
Financial firms, hedge funds, and tech companies that filed PERM applications for quantitative analyst roles in the past two years are far more likely to sponsor again. Use Migrate Mate to filter green-card-sponsoring employers by role type before you apply.
Understand the prevailing wage before negotiating
Your offer salary must meet the DOL-certified prevailing wage for your specific SOC code and work location. Check the OFLC Wage Search before accepting an offer so you know which wage level your credentials support and can negotiate accordingly.
Verify the employer's E-Verify enrollment early
Employers must be E-Verify enrolled to sponsor a PERM-based green card. Confirm this during the interview process, not after an offer, because switching employers mid-petition resets your timeline and requires a new labor certification filing.
Use O*NET to align your job duties with PERM descriptions
PERM job descriptions must reflect the actual minimum requirements for the role, not your personal qualifications. Review the O*NET occupation profile for your quant title to understand how DOL defines the role and ensure your employer's filing language matches.
Account for concurrent filing if priority dates allow
If your country of birth has a current EB-2 or EB-3 priority date, your employer can file the I-140 and I-485 concurrently, letting you apply for work authorization while the green card processes. Confirm current Visa Bulletin dates with USCIS before your employer begins the PERM application.
Green Card Quantitative: Frequently Asked Questions
Do quantitative roles typically qualify for EB-2 or EB-3 sponsorship?
Most quantitative analyst and researcher positions qualify for EB-2 because they require at least a master's degree in mathematics, statistics, computer science, or a related field. Roles with a bachelor's degree minimum can still qualify for EB-2 if the employer accepts a degree plus five years of progressive quant experience as equivalent. EB-3 covers positions where the employer legitimately requires only a bachelor's degree.
How does PERM green card sponsorship differ from H-1B for a quant role?
H-1B visa is a temporary work visa subject to an annual lottery and a six-year cap, while PERM leads to permanent residency with no annual cap at the petition level. The PERM process takes longer upfront because it requires a DOL-supervised recruitment phase before filing, but the outcome is lawful permanent residency rather than a renewable temporary status. For most nationalities, EB-2 and EB-3 priority dates are current, meaning no multi-year backlog.
How long does the full EB-2 or EB-3 process take for a quantitative professional?
The PERM labor certification phase typically runs six to eighteen months depending on whether DOL audits the application. After approval, the employer files the I-140 petition with USCIS, which adds several more months under standard processing. If your priority date is current, you can file for adjustment of status concurrently with the I-140, compressing the overall timeline. Total time from PERM filing to green card approval commonly ranges from two to four years for non-backlogged nationalities.
Where can I find quantitative jobs that offer green card sponsorship?
Migrate Mate lets you search specifically for employers with active EB-2 and EB-3 PERM filing history for quantitative roles, so you spend time on applications where sponsorship is already an established part of the hiring process rather than a negotiation.
Can I change quant employers after my I-140 is approved but before I get my green card?
Yes, under AC21 portability rules, you can change to a same or similar quantitative role with a new employer after your I-140 has been approved and your I-485 has been pending for at least 180 days. The new role must fall under the same or a comparable SOC occupational category. Your priority date stays intact, but the new employer does not need to file a fresh PERM application.