Quantitative Analyst

Quantitative AnalystThe 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.The Quantitative Analyst will:Build and maintain cash-flow projection models for private fund interests, including lifecycle event modeling (capital calls, distributions, NAV evolution) and Monte Carlo simulationImplement and calibrate discount-rate and fair-value methodology against observed secondary-market transaction dataExtend coverage to new vehicle types, including evergreen and interval funds with gated or periodic liquidityProduce scenario analysis (high / base / low), advance rates, and audit-ready valuation outputBuild and maintain the private-market risk factor model: segment-level historical return series, volatility, beta, correlation, value-at-risk, and concentration analyticsImplement historical and hypothetical stress scenarios and portfolio what-if analysisDevelop allocation-versus-limit monitoring and portfolio risk reportingBuild and maintain the front-end and API layers of the platforms, alongside the models behind themRun 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 clientsValidate models through champion–challenger testing, backtesting against realized outcomes, and documented methodology reviewsDocument methodology, design decisions, and code so that any team member can pick up any componentContribute across the other platforms and internal applications as the team's priorities requireWe're looking for someone with:A bachelor's degree in financial engineering, quantitative finance, mathematics, statistics, physics, computer science, or a related quantitative field; master's preferredWorking command of the core toolkit: time value of money, discounted cash flow, NPV and IRR, volatility and correlation estimation, value-at-risk, Monte Carlo simulationSolid statistical foundation: regression, time-series analysis, probability distributions, parameter estimationAbility to read a methodology paper or a fund document and turn it into a working model1–3 years of professional experience writing production Python, including the scientific stack (NumPy, pandas, SciPy)1–3 years of SQL experienceSound object-oriented design and the discipline to write tested, maintainable codeComfortable in Git-based workflowsDocker containerization and AWS cloudPreferred:Master's degree in financial engineering, quantitative finance, or mathematical financeExposure to private markets or alternative assets: fund structures, distribution waterfalls, NAV reporting, secondary transactionsExperience with factor models, stress-testing frameworks, or model validationFamiliarity with financial data providers (such as Preqin, PitchBook, Burgiss, and Bloomberg)Progress toward CFA, FRM, or CAIAExperience 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 APIsLinuxJavaScriptCSSWorking style:Detail-oriented: checks the numbers, tests the edge cases, and doesn't ship something that hasn't been verifiedDependable: 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 needsTakes 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 itBalances rigor with delivery: cares that the model is right, and also that it shipsCommunicates clearly with both technical and non-technical colleaguesFeatured BenefitsMedical, Dental and Vision InsuranceCompany Paid Life and AD&D InsuranceDisability Insurance401k Program with Employer MatchingEqual OpportunityAll 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.