Financial Quantitative Analyst

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2 days ago Requisition

The Quant Engineering and Risk team builds and runs the company’s alternative asset analytics ecosystem end to end — a set of connected pillar platforms covering the alternative-investment decision lifecycle:

• Value Alt — market-calibrated fair-value pricing and advance-rate engine for private fund interests
• Alt Lens — portfolio risk and analytics platform: volatility, beta, value-at-risk, correlation, concentration, and stress testing built on private-market historical returns
• Alt Signal — AI-enabled fund due-diligence and screening platform
• Alt Deal — buyer-side acquisition underwriting and capital-structure analysis platform

We are a small team that owns these client-facing products end to end — methodology, model implementation, data pipelines, APIs, and the web applications — on a Python, Vue.js, and AWS cloud stack. AI-assisted development is a core part of how we build, and we invest deliberately and heavily in wiki documentation and cross-training so that knowledge is shared rather than siloed.

The Financial Quantitative Analyst will design, build, validate, and maintain pricing and risk models for private-market assets, with a primary focus on the Value Alt pricing engine and the Alt Lens risk engine.
The role combines financial engineering with full-stack software development
: you will implement models in production code, calibrate them against market data, validate them against realized outcomes, and build the web applications that put them in front of clients.

The role may extend across the wider ecosystem — deal underwriting in Alt Deal, screening methodology in Alt Signal, and the shared services that connect the products. Seniority and compensation depend on qualifications.

• Build and maintain cash-flow projection models for private fund interests, including lifecycle event modeling (capital calls, distributions, NAV evolution) and Monte Carlo simulation
• Implement and calibrate discount-rate and fair-value methodology against observed secondary-market transaction data
• Extend coverage to new vehicle types, including evergreen and interval funds with gated or periodic liquidity
• Produce scenario analysis (high / base / low), advance rates, and audit-ready valuation output
• Build and maintain the private-market risk factor model: segment-level historical return series, volatility, beta, correlation, value-at-risk, and concentration analytics
• Implement historical and hypothetical stress scenarios and portfolio what-if analysis
• Develop allocation-versus-limit monitoring and portfolio risk reporting

Across the platforms

• Build and maintain the front-end and API layers of the platforms, alongside the models behind them
• Run and improve the quarterly production cycle: data pipelines from public filings and commercial providers, model runs, and the reporting that goes to the board and to clients
• Validate models through champion- challenger testing, backtesting against realized outcomes, and documented methodology reviews
• Document methodology, design decisions, and code so that any team member can pick up any component
• Contribute across the other platforms and internal applications as the team’s priorities require

Financial engineering and quantitative foundation — required

• Bachelor’s degree in financial engineering, quantitative finance, mathematics, statistics, physics, computer science, or a related quantitative field;
  Master’s preferred
• Working command of the core toolkit: time value of money, discounted cash flow, NPV and IRR, volatility and…