Financial Quantitative Analyst

The Beneficient Company Group USA LLC•Dallas, TX

About The Position

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: ValueAlt, AltLens, AltSignal, and AltDeal. 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.

Requirements

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 correlation estimation, value-at-risk, Monte Carlo simulation
Solid statistical foundation: regression, time-series analysis, probability distributions, parameter estimation
Ability to read a methodology paper or a fund document and turn it into a working model
1–3 years of professional experience writing production Python, including the scientific stack (NumPy, pandas, SciPy)
1–3 years of SQL experience
Sound object-oriented design and the discipline to write tested, maintainable code
Comfortable in Git-based workflows
Docker containerization and AWS cloud

Nice To Haves

Master’s degree in financial engineering, quantitative finance, or mathematical finance
Exposure to private markets or alternative assets: fund structures, distribution waterfalls, NAV reporting, secondary transactions
Experience with factor models, stress-testing frameworks, or model validation
Familiarity with financial data providers (such as Preqin, PitchBook, Burgiss, and Bloomberg)
Progress toward CFA, FRM, or CAIA
Experience building web applications — front end and API layer — ideally in Vue.js/Flask, or in a comparable framework (React, Node.js, Jinja2, etc.)
CI/CD pipelines (Bitbucket pipelines or similar)
Experience with AI-assisted development tools (e.g., Claude Code, GitHub Copilot) and LLM APIs
Linux
JavaScript
CSS

Responsibilities

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
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