Quantitative Engineer (Private Markets)

Jobot; San Francisco (CA); On-site; USD 300,000 - 360,000; Full time

Benefits offered by this job

Competitive Base Salary

Extremely Competitive Benefits

Flexible Work Schedules

Accelerated Career Growth

Job summary

Jobot is seeking a Quantitative Engineer (Private Markets) in San Francisco to own models and data infrastructure powering our private-market intelligence platform. You will develop pricing models, build production pipelines, and collaborate with a lean team to deliver client-ready solutions.

The role emphasizes ownership of modeling, data features, and ML-driven data ingestion, with equity and a highly competitive compensation package. On-site four days per week in San Francisco.

Qualifications

• Experience in quantitative finance or data-driven trading environments.
• Strong background in statistics and financial modeling.
• Hands-on experience building production-grade data pipelines.
• Master’s degree or PhD strongly preferred.

Responsibilities

• Model development: build and improve pricing and valuation models for illiquid private-market assets.
• Feature engineering: identify, test, and integrate new financial features and data signals.
• Production pipelines: develop scalable data pipelines for ML models and client products.
• AI innovation: experiment with LLMs to scale data ingestion and QA.
• Client advisory: analyze large proprietary datasets and explain methods to clients.
• Product ownership: collaborate with engineering to shape architecture and roadmap.

Skills

Financial rigor

Mathematics

Data engineering

Machine learning

Communication skills

Education

Data Science / Mathematics / Statistics / CS / Financial Engineering (MS/PhD preferred)

Job description

Quantitative Engineer (Private Markets)

This Jobot Job is hosted by: Jim Quirk

Salary: $300,000 - $360,000 per year

A bit about us

We are an elite, well-funded fintech startup building the foundational data, pricing, and transaction infrastructure for the global private markets. Backed by a $16M Series A from the world’s largest asset managers and investment banks, our platform tracks over $300B in proprietary transaction data and $4T in funding signals for 100,000+ companies. Based in San Francisco, our lean team thrives on technical rigor, deep engineering ownership, and solving complex, multi-trillion-dollar valuation challenges for the world's most sophisticated institutional investors.

Why join us

• Competitive Base Salary!
• Extremely Competitive Benefits!
• Flexible Work Schedules!
• Accelerated Career Growth!

Job Details

Location: San Francisco, CA (In-Office 4 Days/Week)

Compensation: $300,000 – $350,000 + Equity

About the Company

We are a rapidly growing, recently funded Series A fintech company building the data, pricing, and transaction infrastructure for the global private markets. Unlike public equities, private company shares do not trade continuously on centralized exchanges, making accurate pricing and market intelligence extremely difficult to establish. We are solving this challenge by aggregating vast amounts of proprietary secondary-market activity, funding data, and investor signals into a platform used by the world's leading financial institutions. Backed by a $16M Series A round from major global asset managers and investment banks, our platform currently tracks: Over $300 billion in proprietary transaction data; Approximately $4 trillion in historical funding-round data; Comprehensive coverage of more than 100,000 private companies and investors; An elite institutional client base that collectively manages over $52 trillion in assets.

The Opportunity

This is not a traditional internal quantitative role. It is a rare opportunity to apply institutional-quality modeling to proprietary, highly unique private-market data. You will blend rigorous quantitative research with production data engineering and direct customer exposure, enjoying massive ownership within a lean, high-caliber team. As a Quantitative Engineer, you will take full ownership of the models and data infrastructure powering our flagship private-market intelligence products. A primary focus will be our predictive daily pricing engine for actively traded private companies. Because these are illiquid assets without clean, public price discovery, this work requires exceptional creativity and the ability to extract highly accurate signals from complex, imperfect datasets.

Responsibilities

• Model Development: Build, maintain, and continuously improve complex pricing and valuation models for illiquid private-market assets.
• Feature Engineering: Identify, test, and integrate new financial features and data signals to drive model accuracy.
• Production Pipelines: Develop and optimize scalable production data pipelines that support machine learning models and client-facing products.
• AI Innovation: Experiment with Large Language Models (LLMs) to automate and scale data ingestion, entity classification, and automated quality assurance.
• Client Advisory: Analyze massive proprietary datasets to deliver clear insights and join select technical conversations to explain methodology directly to sophisticated financial clients.
• Product Ownership: Collaborate closely with a tight-knit engineering team to materially shape the technical architecture and product roadmap.

Key Requirements

• Financial Rigor: Previous quantitative experience at a trading desk, hedge fund, investment bank, or a similarly rigorous, data-driven financial environment.
• Mathematical Foundation: Strong background in statistics, applied mathematics, financial modeling, machine learning, or quantitative research.
• Technical Stack & Data Engineering: Robust programming skills with hands‑on experience building and maintaining production‑grade data pipelines.
• Communication Skills: Ability to articulate complex technical methodologies and modeling choices clearly to highly sophisticated financial clients.
• Education: Degree in Data Science, Mathematics, Statistics, Computer Science, Financial Engineering, or a closely related field. A Master’s degree or PhD is strongly preferred.
• Location: Must be based in or willing to relocate to San Francisco, working on‑site in the office four days per week.

Why This Role is Compelling

Instead of maintaining a fractional component of a mature, legacy public-market trading system, you will have end‑to‑end ownership over the models, signals, and pipelines defining a completely new asset class infrastructure. Backed by top‑tier institutional investors, this role provides the technical depth of a top hedge fund with the high‑upside equity and velocity of an elite San Francisco startup.

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions.

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