Green Card Quantitative Research Analyst Jobs
Quantitative Research Analyst roles qualify for employment-based green card sponsorship under EB-2 and EB-3, with employers filing PERM labor certification through DOL before advancing to I-140 petition and adjustment of status. Advanced degrees in mathematics, statistics, or economics strengthen EB-2 eligibility, while the PERM process documents that no qualified U.S. worker was displaced.
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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 1,774+ Green Card Quantitative Research Analyst Jobs
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Get Access To All JobsTips for Finding Green Card Sponsorship as a Quantitative Research Analyst
Match your degree to the PERM job description
PERM requires the employer to define minimum qualifications before advertising. If your master's in applied mathematics or financial engineering aligns precisely with those listed requirements, the I-140 petition under EB-2 is far easier to support than a loosely matched credential.
Target employers with active PERM filing history
Quantitative research roles at asset managers, hedge funds, and financial technology firms appear regularly in DOL PERM disclosure data. Searching that data by job title filters your target list to employers who have sponsored similar roles before, not just those who say they will.
Use Migrate Mate to find verified sponsoring employers
Search Migrate Mate to identify Quantitative Research Analyst positions at employers with documented green card filing history. The platform surfaces roles where sponsorship is an established practice rather than a case-by-case negotiation you'd have to initiate yourself.
Clarify EB-2 versus EB-3 at the offer stage
Ask the hiring team which preference category they intend to file under before signing an offer. EB-2 advanced degree petitions skip PERM if an NIW applies, while EB-3 professional filings require the full labor certification process and affect how far back your priority date will need to be current.
Understand how priority dates affect your timeline
For nationals of India and China, EB-2 and EB-3 priority date backlogs can extend wait times significantly beyond the PERM and I-140 stages. Check the monthly Visa Bulletin from DOS before accepting a role, so your expected green card timeline is realistic from day one.
Document your specialized skills for the OFLC Wage Search
PERM prevailing wage determinations use O*NET job zone and SOC code classifications. Quantitative Research Analyst roles typically map to job zone four or five, which affects the wage level DOL certifies. Confirm with your employer that the wage offered meets or exceeds the OFLC Wage Search result for your work location.
Green Card Quantitative Research Analyst: Frequently Asked Questions
Do Quantitative Research Analyst roles typically qualify for EB-2 or EB-3 sponsorship?
Most Quantitative Research Analyst positions qualify for EB-2 because the role normally requires at least a master's degree in mathematics, statistics, economics, or a related quantitative field. Employers can also file under EB-3 for candidates with a bachelor's degree. The category used affects your priority date and, for nationals of oversubscribed countries, your wait time before a green card becomes available.
How does green card sponsorship differ from H-1B for this role?
H-1B visa provides temporary work authorization subject to an annual lottery, while an employment-based green card through PERM leads to permanent residency with no renewal cycle. There is no annual cap on EB-3 filings at the petition stage, so your employer can start the PERM process at any point in the year. The tradeoff is that PERM and I-140 together typically take one to three years before a priority date becomes current.
What does the PERM labor certification process require for a quant analyst position?
The employer must conduct a DOL-supervised recruitment campaign demonstrating no qualified U.S. worker was available for the role. For Quantitative Research Analyst positions, job postings must reflect the actual minimum requirements the employer uses in practice, including degree field and any specialized skills like statistical modeling or programming languages. Inflated requirements or inconsistencies between the job ad and the actual role can trigger an audit.
Where can I find Quantitative Research Analyst jobs that offer green card sponsorship?
Migrate Mate lets you filter Quantitative Research Analyst roles by employers with verified employment-based green card filing history, so you're not spending time on positions where sponsorship is unlikely. Looking at DOL PERM disclosure data directly is another way to identify firms that have previously sponsored this job title, which signals an established internal process rather than a one-off situation.
Can a Quantitative Research Analyst self-petition for a green card without employer sponsorship?
Yes, under the National Interest Waiver (NIW) category within EB-2, you can file an I-140 without an employer's involvement if your research contributes to a U.S. national interest. Quantitative researchers whose work influences financial stability, public health modeling, or critical infrastructure analysis have pursued this path. USCIS evaluates NIW petitions on a case-by-case basis using a three-part framework, and approval is not guaranteed.