Vice President, Research

Ellington Management Group, LLC; New York (NY); On-site; USD 180,000 - 320,000; Full time

Job summary

Ellington Management Group, LLC in New York seeks a Vice President, Research to lead the firm's quantitative risk, valuation, and collateral modeling efforts. You will architect scalable modeling infrastructure and guide analyses for investment decisions.

Requirements include a Bachelor’s degree in a quantitative field and 2 years in a related role, with hands-on experience in Intex, Python, and C++. You will collaborate with portfolio managers and traders, ensuring documentation and governance

Qualifications

• Bachelor’s degree or foreign equivalent in a quantitative field such as Computer Science, Economics or Finance.
• 2 years of experience as a Research Analyst, Quantitative Analyst, or related role.
• Experience with quantitative risk, valuation and collateral modeling for structured finance products.

Responsibilities

• Oversee development, implementation, and enhancement of quantitative risk, valuation, and collateral modeling infrastructure.
• Architect and lead the collateral modeling framework for scalability, accuracy, and governance.
• Develop quantitative models for structured finance products, including mortgage-backed securities, using Intex and related subroutines to generate OAS-based cashflow and valuation models.
• Lead AI/ML-enhanced systems to monitor and optimize profitability of loan origination and securitization activities.
• Lead AI-enhanced tools to support trading desk workflows and improve decision-making.
• Ensure models adhere to documentation, validation, and governance standards; review work for accuracy and consistency.
• Apply statistical and econometric techniques to analyze markets, model asset performance, and inform investment decisions.
• Integrate internal and third-party market data into calibration processes and evaluate external data for modeling.
• Collaborate with portfolio managers, traders, and senior researchers to identify business needs and develop quantitative solutions.
• Coordinate research initiatives and modeling enhancements across the team; prepare analyses for clients and investors.
• Assist in responding to technical inquiries in coordination with management and investor relations.
• Participate in recruitment and evaluation of research personnel.

Skills

Quantitative risk

Valuation

Collateral modeling

Python

C++

AI/ML

Model governance

Data integration

Education

Bachelor’s degree in Computer Science, Economics, Finance, or related field

Tools

Intex

Python

C++

Job description

Position: Vice President, Research

Location: 711 Third Avenue, 5th Floor, New York, NY 10017

Job Duties: Oversee the development, implementation, and enhancement of the firm’s quantitative risk, valuation, and collateral modeling infrastructure. Architect and lead the development of the firm’s collateral modeling framework, ensuring scalability, accuracy, and alignment with business and regulatory requirements. Develop, implement, and maintain quantitative models for structured finance products, including mortgage-backed securities, utilizing industry-standard tools such as Intex and related subroutines to generate OAS-based cashflow and valuation models. Lead the design and development of AI/ML-enhanced systems to monitor and optimize the profitability of loan origination and securitization activities. Lead the development of AI-enhanced analytical tools to support trading desk workflows and improve efficiency and decision-making. Ensure that all models adhere to established best practices, including appropriate documentation, validation, and governance standards. Review and evaluate modeling work produced by research team members to ensure consistency, accuracy, and adherence to quantitative and scientific standards. Apply statistical, econometric, and quantitative techniques to analyze financial markets, model asset performance, and inform investment decisions. Assess and integrate internal and third-party market data into model calibration processes; evaluate external vendor data and incorporate such data into existing modeling frameworks as appropriate. Monitor and analyze market developments, regulatory guidance, and industry best practices related to financial modeling; review relevant academic and industry research. Collaborate with portfolio managers, traders, and senior research staff to identify business needs and develop quantitative solutions to support investment strategies. Coordinate and oversee the implementation of research initiatives and modeling enhancements across the research team. Prepare and review technical materials and analyses for internal stakeholders and external parties, including clients and prospective investors. Assist in responding to technical inquiries from clients and prospective investors in coordination with senior management and investor relations. Participate in the recruitment and evaluation of research personnel, including conducting interviews, assessing candidate qualifications, and providing hiring recommendations.

Job Requirements: Must have a Bachelor’s degree, or foreign equivalent, in Computer Science, Economics, Finance, or a closely related quantitative field. Must have 2 years of experience as a Research Analyst, Quantitative Analyst, or a related role. The 2 years of experience must include experience with: quantitative risk, valuation, and collateral modeling for structured finance products, including mortgage-backed securities and related instruments; Intex and Intex subroutines for constructing and analyzing OAS-based cashflow and valuation models; statistical, econometric, and quantitative modeling techniques for financial market and asset performance analysis; analysis of large-scale financial and market datasets, including integration of internal and third-party data sources into model calibration and validation processes; programming in Python, C++, or similar languages for model development, data analysis, and system implementation; model performance evaluation and application of modeling best practices, including documentation, validation, and governance standards; and design and implementation of quantitative solutions supporting investment strategies.