Pay
$118K–$193K is typical
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From 3,721 postings in the last year. Stated ranges, not salaries paid.
Quantitative Analyst
Dallas, TX, US
Live, first seen by us 29 days ago- Pay
- Pay not listedSimilar roles state $118K–$193K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingThe Quantitative Analyst will design, build, validate, and maintain pricing and risk models for private-market assets, with a primary focus on the ValueAlt pricing engine and the AltLens risk engine.
This is not a financial analyst, business analyst, data analyst, data scientist, risk analyst, financial modeler, or quant researcher role, and it is not for ad-hoc scripting, spreadsheet modeling, reporting, or research.
Build and maintain cash-flow and fair-value models for private fund interests
Build and maintain the private-market risk factor model and VaR analytics
Run the quarterly production cycle from data pipelines through board and client reporting
Validate models through champion–challenger testing and backtesting
Build and maintain front-end and API layers alongside the models
From the employer’s posting
The Quantitative Analyst will design, build, validate, and maintain pricing and risk models for private-market assets, with a primary focus on the ValueAlt pricing engine and the AltLens 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.
This is not a financial analyst, business analyst, data analyst, data scientist, risk analyst, financial modeler, or quant researcher role, and it is not for ad-hoc scripting, spreadsheet modeling, reporting, or research. This is an engineering role that requires a strong foundation in quantitative finance. Most of your time will be spent designing, coding, testing, and shipping production-quality systems end to end — quantitative models, data pipelines, APIs, and client-facing web applications in a cloud environment.
Build and maintain cash-flow projection models for private fund interests
Build and maintain the private-market risk factor model: segment-level historical return series, volatility, beta, correlation, value-at-risk, and concentration analytics
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
Build and maintain the front-end and API layers of the platforms, alongside the models behind them
About Beneficient
Beneficient (Nasdaq: BENF) provides liquidity and primary capital solutions, trust and custody services, and technology to holders of alternative assets — including private equity, venture capital, real estate, private credit, and secondary interests.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 7, 202629 days ago
- Recorded sightings
- 24
- Last seen by us
- Nov 5, 2026
- Employer says posted
- Oct 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 29
Similar jobs usually come down between day 7 and day 56.
From 10,204 similar postings that came down. Coming down is not always a hire.
Beneficient is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- JavaScript
- Python
- SQL
- AWS
- Docker
- Flask
- NumPy
- pandas
- React
- SciPy
- Node.js
Where the posting names them
- Linux - JavaScript - CSS
- AltDeal — 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. Position Summary
Technical — required - 1–3 years of professional experience writing production Python, including the scientific stack (NumPy, pandas, SciPy) - 1–3 years of SQL experience
- 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 Preferred
- 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)
Your next step
Complete your application on workforcenow.adp.com. The employer’s form will show what is required.
Already applied? Track this application
About Beneficient
- People
- About 50 in 2026, down 9% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as BENF.
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
About Beneficient
Beneficient (Nasdaq: BENF) provides liquidity and primary capital solutions, trust and custody services, and technology to holders of alternative assets — including private equity, venture capital, real estate, private credit, and secondary interests. Alongside its financial services business, Beneficient is building alternative asset technology platforms for family offices, small institutions, and lenders. Further information is available at www.trustben.com.
About the Team
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 — market-calibrated fair-value pricing and advance-rate engine for private fund interests
- AltLens — portfolio risk and analytics platform: volatility, beta, value-at-risk, correlation, concentration, and stress testing built on private-market historical returns
- AltSignal — AI-enabled fund due-diligence and screening platform
- AltDeal — 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.
Position Summary
The Quantitative Analyst will design, build, validate, and maintain pricing and risk models for private-market assets, with a primary focus on the ValueAlt pricing engine and the AltLens 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.
This is not a financial analyst, business analyst, data analyst, data scientist, risk analyst, financial modeler, or quant researcher role, and it is not for ad-hoc scripting, spreadsheet modeling, reporting, or research. This is an engineering role that requires a strong foundation in quantitative finance. Most of your time will be spent designing, coding, testing, and shipping production-quality systems end to end — quantitative models, data pipelines, APIs, and client-facing web applications in a cloud environment.
What You’ll Do
Pricing — ValueAlt
- 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
Risk — AltLens
- 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
What We’re Looking For
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 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
Technical — required
- 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
Preferred
- 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
Working style
- Detail-oriented: checks the numbers, tests the edge cases, and doesn’t ship something that hasn’t been verified
- Dependable: can be handed a piece of work and trusted to deliver it well independently — and raises a flag early when something is at risk. In a small team, everyone has to be someone the rest can count on.
- Collaborative and quick to learn: asks good questions, shares knowledge, reviews others’ work, and picks up whatever the team needs
- Takes initiative and ownership: sees what needs doing and does it, owns a component end to end, and documents it so they don’t have to be the only one who knows it
- Balances rigor with delivery: cares that the model is right, and also that it ships
- Communicates clearly with both technical and non-technical colleagues
Featured Benefits
- Medical, Dental and Vision Insurance
- Company Paid Life and AD&D Insurance
- Disability Insurance
- 401k Program with Employer Matching
Equal Opportunity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, disability, sexual orientation, national origin, or any other category protected by law.
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- Location & working pattern
Dallas, TX, US
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