Quant Engineer

Leoforce; San Francisco (CA); Sur place; USD 300 000 - 400 000; Plein temps

Avantages offerts par ce poste

Equity

Résumé du poste

Leoforce in San Francisco seeks a Quant Engineer to build and refine pricing models for illiquid assets and to develop the data infrastructure powering our models and platform. You will own model development, data pipelines, and collaboration with cross-functional teams in a high-growth fintech setting.

The role emphasizes hands-on quantitative finance, machine learning, and data engineering, with significant ownership and direct impact on institutional clients.

Qualifications

• Professional experience as a Quant at a trading desk or comparable institutional finance environment.
• Strong foundation in statistics, probability, applied mathematics, financial modeling, or ML.
• Degree in a quantitative field; master's preferred.

Responsabilités

• Build, maintain, and improve quantitative pricing models for illiquid assets.
• Research new datasets, features, and market signals to improve model performance.
• Design and build pipelines that collect, parse, validate, and store financial data.
• Develop ML systems using structured and unstructured data.
• Experiment with LLMs to automate data ingestion, extraction, and QC workflows.
• Improve the scalability and efficiency of existing data pipelines.
• Produce custom analyses and data deliverables for institutional clients.
• Explain quantitative methodologies and data-collection strategies during client conversations.
• Collaborate with engineering, product, sales, and leadership.

Connaissances

Statistical foundations

Probability

Applied mathematics

Financial modeling

Machine learning

Data engineering

Formation

Master's degree preferred

Math/Statistics degree

Outils

Python

NumPy/Pandas

ML frameworks

Description du poste

Quant Engineer

6967148

4 days ago

Job Description

Experience: Mid Level Salary: $300,000 - $400,000 per year

Job Details

As a Quant Engineer, you will build and improve pricing models for illiquid private-market assets while developing the data infrastructure that supports our models and customer-facing platform.

Responsibilities

• Build, maintain, and improve quantitative pricing models for illiquid assets
• Research new datasets, features, and market signals that can improve model performance
• Design and build pipelines that collect, parse, validate, and store financial data
• Develop machine-learning systems using structured and unstructured datasets
• Experiment with LLMs to automate data ingestion, extraction, and quality-control workflows
• Improve the scalability and efficiency of existing data pipelines
• Produce custom analyses and data deliverables for institutional clients
• Explain quantitative methodologies and data-collection strategies during select client conversations
• Collaborate closely with engineering, product, sales, and company leadership

Qualifications

• Professional experience as a Quant at a trading desk, hedge fund, bank, asset manager, or comparable institutional financial environment
• Strong foundation in statistics, probability, applied mathematics, financial modeling, or machine learning
• Degree in mathematics, statistics, data science, computer science, financial engineering, or another quantitative discipline
• Master's degree preferred
• Strong software-engineering and data-engineering capabilities
• Experience working with large, complex, or imperfect financial datasets
• Ability to translate technical concepts for both quantitative and non-technical audiences
• Comfortable operating with significant ownership in an early-stage environment
• Able to work from our San Francisco office four days per week

A bit about us

Location: San Francisco, CA

Work Model: Four days per week in office

Compensation: $300-400K + Equity

About Us

We are an early-stage financial technology company building data, pricing, and research infrastructure for the private markets.

Our platform transforms complex and fragmented market information into actionable pricing and investment intelligence for leading asset managers, investment banks, venture funds, and other sophisticated financial institutions.

Following a recently completed Series A financing, we are expanding our quantitative and data capabilities as we build foundational infrastructure for a rapidly growing asset class.

Why join us

Private assets do not have the transparent exchanges, continuous pricing, or standardized datasets available in the public markets. Solving that problem requires sophisticated quantitative modeling, creative feature development, and robust data infrastructure.

As our Quant Engineer, you will have substantial ownership over the models and systems powering our core products. You will work with proprietary financial datasets, solve complex pricing problems, and see your work used directly by major financial institutions.

This is an opportunity to combine quantitative finance, machine learning, data engineering, and customer-facing problem-solving within a small and highly capable team.

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