Lead Quant — Market Microstructure & Securities Lending at The Voleon Group

Berkeley, California, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Finance, Investment ManagementIndustries

Requirements

5+ years in a quantitative trading environment
Strong programming in Python, R, and SQL; ability to write production code and work well across teams
Applied statistics (valid tests on real-world data); clear quantitative reasoning
Deep market microstructure knowledge and passion for markets
Excellent communication
Nice to have
Experience with securities lending / equity finance / portfolio financing (e.g., stock-loan, TRS, repo), and/or TCA/market-impact analysis
kdb+/q or C++
Experimentation (A/B, randomized trials) for market workflows

Responsibilities

Lead and mentor a small team of Quantitative Trading Strategists and Data Scientists
Research market questions across asset classes; create clear analyses and present findings across teams
Build production-quality code (Python/R/SQL): packages, data pipelines, and trading applications
Partner with Trading & Research to improve strategy implementation and market interaction
Provide domain expertise in market microstructure; manage relationships with brokers and trading partners
Evaluate order placement and liquidity access (e.g., venue usage, routing, and tactics) as part of broader market implementation

Skills

Key technologies and capabilities for this role

Machine LearningQuantitative AnalysisMarket MicrostructureSecurities LendingAlgorithmic TradingStatistical ModelingData ScienceTrading StrategiesPortfolio Financing

Questions & Answers

Common questions about this position

What compensation and benefits does this role offer?

The role offers competitive pay and benefits.

Is this position remote-friendly, and what's the location policy?

The position is remote-friendly with a Berkeley hub.

What skills are required for the Lead Quant role?

Required skills include 5+ years in a quantitative trading environment, strong programming in Python, R, and SQL, applied statistics with valid tests on real-world data, deep market microstructure knowledge, and excellent communication.

What is the company culture like at Voleon?

You'll work with internationally recognized experts in machine learning research, highly experienced finance and technology professionals, and collaborate across Trading and R&D teams on high-impact ML-driven strategies.

What makes a strong candidate for this Lead Quant position?

Strong candidates have 5+ years in quantitative trading, production-level programming in Python/R/SQL, deep market microstructure expertise, applied statistics skills, and excellent communication; nice-to-haves include securities lending experience and kdb+/q or C++.

The Voleon Group

Investment management using machine learning algorithms

About The Voleon Group

Voleon focuses on investment management by utilizing machine learning to analyze financial market trends. The firm uses advanced statistical models to process large datasets and identify patterns that inform investment decisions, setting it apart from traditional methods that rely on human intuition. Voleon serves institutional clients and operates on a performance-based fee structure, aligning its interests with those of its clients. The company's goal is to provide data-driven insights that optimize investment returns while adapting to changing market conditions.

Berkeley, CaliforniaHeadquarters

2007Year Founded

VENTURE_UNKNOWNCompany Stage

Quantitative Finance, Financial ServicesIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

Life Insurance

Paid Vacation

Paid Sick Leave

401(k) Retirement Plan

401(k) Company Match

Risks

Competition from other quantitative hedge funds may erode Voleon's market share.

Regulatory scrutiny on AI use in finance could increase compliance costs for Voleon.

Data quality issues could lead to inaccurate predictions and financial losses for Voleon.

Differentiation

Voleon uses machine learning for data-driven financial market predictions.

The firm serves institutional clients with a focus on scalability and risk management.

Voleon's academic approach emphasizes intellectual rigor and continuous learning.

Upsides

Increased interest in ESG investing offers new opportunities for Voleon's models.

Alternative data sources enhance predictive models for quantitative hedge funds like Voleon.

Cloud computing enables efficient scaling of Voleon's data processing capabilities.

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