Quantitative Analyst Legal & Financial Structures

Sterlington; Lisboa; A distancia; EUR 119.000 - 237.000; Jornada completa

Descripción de la vacante

Sterlington PLLC is seeking a quantitatively rigorous analyst to model complex deal structures and executive compensation from a numerical perspective. This 100% remote independent contract role sits with the Corporate/M&A practice and involves AI-enabled workflows.

You will work directly with the head of the practice and senior partners, building and stress-testing analytical models, exploring value drivers, and translating math into practical deal insights.

Formación

• PhD or Master’s in a quantitative field as stated.
• Experience with AI tools in a professional context.
• Ability to work independently in a remote, high-performance environment.
• Strong numerical and analytical skills.

Responsabilidades

• Integrate AI-assisted workflows into day-to-day work.
• Model complex business and executive compensation structures.
• Stress-test assumptions and assess risk.
• Build analytical models used on live client matters.

Conocimientos

Analytical thinking

Strong judgment

Independent work

AI fluency

Educación

PhD or Master’s in Mathematics/Applied Mathematics/Finance

Herramientas

AI modeling tools

Excel

Descripción del empleo

Quantitative Analyst Legal & Financial Structures

Reports to: Head of Corporate/M&A Practice

Department: Corporate/M&A

Location: 100% Remote

Working Hours: Eastern Standard Time (EST)

Contract type: Independent Contract

Our Firm

Sterlington PLLC is a full-service law firm focusing on complex corporate, litigation, executive compensation, and private wealth matters. As a firm, we focus on the economic as well as the legal aspects of our matters.

Sterlington not only documentsdeals,wecut deals for clients. As part of that, we play somethingcloseto a financial / banker role in analyzing deal structures and executive compensation arrangements.We are looking for someonewho can help us model and understand transactions and executive compensation arrangements from a numerical perspective. Our philosophy is that we need peopletrained to thinklogically and systematically,and equipped tooperatewith modernanalysistools(highexpertisein AI modeling and Excel).

This role sits at the intersection of math, finance, law, and business , and is designed for someone who is intellectually rigorous and genuinely enjoys untangling complexity. You will work directly with thehead of the corporate / M&A practice,and senior partnersin those practices .

This is a rare opportunity for a mathematicallyand financiallydisciplined thinker whocombinesfirst-principles reasoning with AI fluency, applying both to high-stakes, real-world situations alongside individualsoperatingat the highest levels of decision-making.

What You’ll Do

• Integrate AI-assisted workflows into your day-to-day work to enhance speed, depth, and accuracy of analysis
• Analyze and model complex business, executive compensation, structure and financial arrangements to extract underlying economic logic and value drivers
• Map ownership, incentive, and value-distribution structures across multiple scenarios
• Stress-test assumptions and identify points of economic sensitivity and hidden risk
• Build and refine analytical models and frameworks used on live client matters
• Contribute to the evolution of AI-enabled analytical practices within the firm

What Success Looks Like

• Your analysis directly informs structuring decisions, negotiations, and risk assessment
• You demonstrate strong judgment in separating signal from noise in dense materials
• You effectively integrate AI into your workflow , using it to enhance — not replace — your reasoning

What We’re Looking For

• PhD orMaster’s degree in Mathematics , Applied Mathematics, finance,or a closely related quantitative field
• Expertise in using AI tools in a professional context tomodel andanalyze data
• Comfortable operating independently in a remote, high-performance environment
• Strong judgment
• Prior experience in law is not required.