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Financial Modelling Specialist

Pavago · United States · United States

Remote Full time Posted Open until 19 Oct 2026
  • Remote Position Type: Full-Time, Remote — job description

The job, in the employer's words

Job Title: Financial Modelling Specialist

Position Type: Full-Time, Remote

Working Hours: U.S. client business hours (aligned with prospect time zones and outreach cadences)

About Pavago

Pavago is a global recruitment partner specialising in placing top-tier offshore talent with fast-growing U.S. companies. Our clients expect precision, ownership, and world-class standards from day one. We source elite, high-agency professionals who can work independently, think critically, and operate at a U.S. accounting and financial analysis standard.

We are hiring a Financial Modelling Specialist for a client, who is backed by YC (W 25 ), building an advanced financial and business modelling infrastructure used to train AI systems.

Key Responsibilities

  • Build complete, end-to-end financial and business models for internal AI training workflows.
  • Review and refine models built by other analysts for structure, clarity, and accuracy.
  • Collaborate with the client’s internal team to improve modelling frameworks and documentation.
  • Participate in regular working sessions to align on modelling standards.
  • (Optional) Provide structured feedback to junior analysts when needed.

Requirements

  • 3–7+ years of hands-on financial modelling experience, ideally across multiple industries or business models.
  • Strong command of U.S.-standard accounting, including:
    • GAAP principles
    • Revenue recognition
    • Cash flow alignment
    • Accrual vs. cash accounting
    • Forecasting & variance analysis
  • Preferred backgrounds:
    • Investment Banking
    • Private Equity
    • FP&A / Strategic Finance
    • Corporate Finance / Consulting
    • Accounting + modelling hybrid roles
  • Advanced Excel / Google Sheets capability; able to build, audit, and optimise complex models.
  • High agency: thrives with loose direction and can create structure independently.
  • Strong communication skills — clear explanation of assumptions, logic, and model decisions.
  • Bonus: experience with structured data work, labelling, or AI training datasets.

What the Day-to-Day Looks Like

  • Take on new modelling assignments with broad instructions and turn them into clean, structured outputs.
  • Build or refine detailed models (operating models, forecasting, scenario analysis, KPI frameworks, etc.).
  • Review peer models, identify issues, and propose improvements.
  • Join short recurring check-ins with the team to maintain consistency and refine standards.
  • Update frameworks, templates, and modelling documentation as needed.
  • This is focused, analytical work that rewards precision and clear thinking.

Interview Process

  • Initial Phone Screening – Quick review of background, communication, and fit.
  • Zoom Interview with Pavago’s HR Team – Deep dive on experience and expectations.
  • Short Assignment – A brief modelling task to evaluate structure and fundamentals.
  • 15-Minute Sync with Client Company – Quick alignment on role, expectations, and communication style.
  • Extensive Modelling Assignment – A more detailed task assessing analytical depth, logic, and modelling quality.
  • Final Interview with Client Team – Walkthrough of your approach and problem-solving style.
  • Offer & Background Check – Final step before onboarding.

#LI-AG1

Requirements mentioned

  • 3–7+ years of hands-on financial modelling experience, ideally across multiple industries or business models.
  • Strong command of U.S.-standard accounting, including:
  • Preferred backgrounds:
  • Advanced Excel / Google Sheets capability; able to build, audit, and optimise complex models.
  • High agency: thrives with loose direction and can create structure independently.
  • Strong communication skills — clear explanation of assumptions, logic, and model decisions.
  • Bonus: experience with structured data work, labelling, or AI training datasets.

No Mondays shows this listing as the employer published it. Check the details on the employer's site before you apply.

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