Job Description
Position Summary: 

Hudson Advisors is seeking a Summer Quant Analyst (Intern) to join its U.S. Residential Credit investment platform in New York. Hudson Advisors is the dedicated asset manager for the Lone Star Funds, which manages multiple billions of dollars of AUM across private equity strategies. The U.S. Residential Credit team focuses on the underwriting, acquisition, and active management of mortgage whole loans and structured credit investments through Lone Star Residential Mortgage Fund IV.

Interns will work directly with the underwriting and investment team to develop and enhance financial models, evaluate performance data, and support pricing, risk assessment, and portfolio construction decisions. The role provides hands-on exposure to large-scale loan-level datasets, structured credit analytics, and the application of statistical and machine learning techniques within an institutional investment framework. Responsibilities include building and refining data-driven and AI-enabled tools to address complex modeling, analytics, and research problems, as well as automating portfolio monitoring and reporting processes.

Interest in MBS/ABS (Mortgage/Asset-Backed Securities) and residential or consumer credit is preferred. The ideal candidate will have a strong quantitative background (e.g., mathematics, statistics, engineering, computer science, or finance), advanced Excel proficiency, and programming experience in languages such as Python, R, or SQL. Familiarity with AI-assisted development environments and modern analytical workflows is a plus. The candidate should be comfortable working with large datasets and applying analytical rigor in a fast-paced investment environment.

 

Pay:

$35 dollars per hour in New York 
 

Duration:

This temporary assignment is for an approximate duration of 10 weeks, beginning on or about June 1st  2026 and ending on or about August 7th 2026. 
 

Essential Functions: 

Support the investment team on ad hoc quantitative analyses and data-driven initiatives related to underwriting, pricing, and portfolio management.
Contribute to the development and enhancement of next-generation investment infrastructure, including scalable data pipelines, analytics tools, and internal reporting systems.
Assist with loan-level cash flow modeling, performance analysis, scenario testing, and return attribution.
Support the investment screening process by conducting structured data studies, analyzing large datasets, and helping refine credit and pricing parameters.
Prepare analytical materials, charts, and presentation content for internal meetings and investment committee discussions.
Participate in meetings with the investment team, counterparties, and other stakeholders to support diligence and portfolio monitoring efforts.
 

Required Knowledge, Skills and Abilities:

Strong analytical, quantitative, and problem-solving skills, with a demonstrated interest in financial markets, credit investing, and data-driven decision making.
Demonstrated programming experience, with proficiency in one or more of the following: Python, SQL, or VBA. Experience building analytical tools, automation workflows, or data pipelines is strongly preferred.
Comfort working with large, loan-level or structured datasets, including data cleaning, transformation, analysis, and extracting actionable insights.
Advanced proficiency in Microsoft Excel (complex formulas, lookups, PivotTables, structured modeling) and PowerPoint.
Familiarity with statistical, machine learning, or business intelligence tools (e.g., Power BI, Tableau, R, MATLAB, Databricks, or similar platforms) is a plus.
Experience leveraging AI-assisted development environments or modern analytical workflows to improve research, modeling, or coding efficiency is a plus.
Highly motivated, detail-oriented, and intellectually curious, with a willingness to take ownership of projects and improve existing processes.
Strong written and verbal communication skills, with the ability to clearly explain quantitative analyses and defend assumptions.
Ability to operate both independently and collaboratively in a fast-paced, deadline-driven investment environment while managing multiple priorities
 

Required Education:

Currently pursuing a Bachelor’s degree in a quantitative or STEM discipline (e.g., Mathematics, Statistics, Physics, Computer Science, Engineering, or a related field).
Expected graduation between December 2027 and June 2028.