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Junior Quantitative Jobs in California (NOW HIRING)

PhD preferred * 2-5 years of relevant experience as a commodity quant supporting a sell-side trading desk or a quantitatively oriented asset manager; exceptional junior candidates with directly ...

PhD preferred * 2-5 years of relevant experience as a commodity quant supporting a sell-side trading desk or a quantitatively oriented asset manager; exceptional junior candidates with directly ...

The Junior Biostatistician supports data engineering, statistical analysis, and analytics functions ... EDUCATION: Bachelor's degree with one to two (1-2) years' experience in quantitative science ...

... Levels: Jr. - Mid Level Clearance: Active Security Clearance (Secret or higher) is preferred ... Bachelor's degree in a quantitative field such as engineering or mathematics (e.g. Electrical ...

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Junior Quantitative information

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How much do junior quantitative jobs pay per hour?

As of Aug 31, 2026, the average hourly pay for junior quantitative in California is $26.60, according to ZipRecruiter salary data. Most workers in this role earn between $16.15 and $32.74 per hour, depending on experience, location, and employer.

What is a junior quantitative?

Junior Quantitatives, often called 'junior quants,' are entry-level professionals who use mathematical, statistical, and computational methods to analyze financial data and develop models for trading, risk management, or investment strategies. They typically work under the supervision of senior quants in financial institutions, such as investment banks, hedge funds, or asset management firms. Their responsibilities often include data analysis, model development, programming, and assisting in the implementation of quantitative strategies. Junior quants usually have strong backgrounds in mathematics, statistics, finance, or computer science. This role is a starting point for building a career in quantitative finance.

What are the key skills and qualifications needed to thrive as a junior quantitative analyst, and why are they important?

To thrive as a Junior Quantitative Analyst, you need strong analytical skills, a solid background in mathematics or statistics, and at least a bachelor's degree in a quantitative field such as mathematics, statistics, finance, or engineering. Familiarity with programming languages like Python, R, or MATLAB, as well as proficiency in Excel and experience with data analysis tools, is typically required. Attention to detail, problem-solving abilities, and effective communication skills help you translate complex analyses into actionable insights. These skills and qualifications are crucial for building accurate financial models, supporting decision-making, and contributing meaningfully to data-driven teams.

What are some common challenges faced by junior quantitative analysts in their first year, and how can they overcome them?

Junior Quantitative Analysts often encounter challenges such as adapting to the fast-paced environment, bridging the gap between academic theory and practical application, and mastering company-specific tools and large datasets. Building strong communication with senior team members and proactively seeking feedback can help overcome these hurdles. Additionally, dedicating time to learn the firm's proprietary systems and collaborating closely with cross-functional teams—like traders and software engineers—will accelerate both skill development and confidence in the role.

What is the difference between Junior Quantitative vs Quantitative Analyst?

AspectJunior QuantitativeQuantitative Analyst
Required CredentialsBachelor's degree in math, finance, or related field; some internshipsBachelor's or master's degree; often more experience or certifications
Work EnvironmentEntry-level, supportive team, learning-focusedMore independent, project-driven, higher responsibility
Employer & Industry UsageFinancial firms, hedge funds, banksFinancial institutions, asset management, hedge funds

The main difference between Junior Quantitative and Quantitative Analyst roles lies in experience and responsibility. Junior Quantitative positions are entry-level, focusing on learning and supporting senior staff, while Quantitative Analysts handle more complex analysis and decision-making. Both roles are common in finance and share similar educational backgrounds, but the level of experience and independence distinguishes them.

Is a junior quantitative an entry level job?

A junior quantitative role is typically considered an entry-level position in finance or data analysis, often requiring a bachelor's degree in a related field and some programming or statistical skills. It is designed for candidates with limited professional experience and provides training to develop technical expertise in quantitative methods.

What is the salary of a junior quantitative researcher?

The salary of a junior quantitative researcher typically ranges from $60,000 to $90,000 annually, depending on the location, industry, and level of experience. Entry-level roles often require proficiency in programming languages like Python or R and strong analytical skills.

What are the most commonly searched types of Quantitative jobs in California?

The most popular types of Quantitative jobs in California are:

What are popular job titles related to Junior Quantitative jobs in California?

For Junior Quantitative jobs in California, the most frequently searched job titles are:

What job categories do people searching Junior Quantitative jobs in California look for?

The top searched job categories for Junior Quantitative jobs in California are:

What cities in California are hiring for Junior Quantitative jobs?

Cities in California with the most Junior Quantitative job openings:

Infographic showing various Junior Quantitative job openings in California as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 71% Physical, 6% Hybrid, and 23% Remote job distribution, with an average salary of $55,334 per year, or $26.6 per hour.

Senior Quantitative Researcher - Risk Modeling

Swish Analytics

San Francisco, CA

Full-time

Re-posted 18 days ago


Job description

Company Description
Swish Analytics is a sports analytics and trading company building the next generation of predictive sports analytics and exchange-based trading products. We believe that profitable trading is a challenge rooted in engineering, mathematics, and market expertise—not intuition. We're seeking team-oriented individuals with an authentic passion for quantitative trading who can execute in a fast-paced environment without sacrificing technical excellence.

As we expand our presence on betting exchanges, we're building infrastructure and strategies akin to those found in traditional financial markets. Our challenges are unique, and we hope you're comfortable in uncharted territory.

Role Overview
As a Senior Quantitative Researcher, you will own end-to-end research and production pipelines for one or more trading strategies. You'll lead research initiatives that generate alpha and improve execution quality, mentor junior researchers, and collaborate closely with our Trading desk to translate quantitative insights into profitable systematic strategies while maintaining rigorous risk management.

Core Responsibilities

  • Own end-to-end research and production pipelines for a strategy

  • Lead alpha research initiatives leveraging advanced statistical and machine learning techniques

  • Process and analyze high-frequency tick data, order book snapshots, and market microstructure signals with sub-millisecond latency requirements

  • Analyze price formation, market liquidity dynamics, and limit order book imbalances across electronic venues

  • Build and run Monte Carlo simulations to estimate P&L distributions, risk exposures, and portfolio dynamics

  • Develop, backtest, and optimize quantitative trading strategies with rigorous statistical validation

  • Interpret complex model outputs and communicate alpha generation mechanisms to portfolio managers

  • Write modular, clean, and efficient Python code; build custom analytics libraries and research frameworks

  • Lead design reviews and establish data quality and research reproducibility standards

  • Guide 1–2 junior researchers through project delivery and model development

  • Proactively engage with traders and infrastructure teams to clarify research objectives and resolve data dependencies

Risk Modeling

  • Design and maintain real-time risk monitoring systems across multi-asset portfolios

  • Build models for dynamic position sizing, portfolio optimization, and factor exposure management

  • Develop stress testing and scenario analysis frameworks for tail-risk events and regime changes

  • Collaborate with Trading and Risk Management to define VaR limits, leverage constraints, and implement automated risk controls

Requirements

  • Minimum of 5 years of experience in quantitative research, systematic trading, or statistical modeling

  • Master's degree in a quantitative discipline (Mathematics, Statistics, Physics, Computer Science, Financial Engineering) strongly preferred; PhD a plus

  • Expert-level Python skills; able to build production-grade research and trading systems

  • Strong SQL skills; experience with complex queries on tick databases and time-series datasets

  • Deep experience with Monte Carlo methods, stochastic calculus, and probabilistic modeling

  • Proven ability to develop, backtest, and deploy systematic trading strategies with demonstrable P&L

  • Experience processing high-frequency tick data and real-time market feeds

  • Familiarity with AWS or similar cloud infrastructure for large-scale backtesting and research

  • Track record of mentoring junior quantitative researchers

  • Excellent communication skills; ability to present complex quantitative research to portfolio managers and trading desks

  • Experience designing enterprise-grade risk management systems with real-time Greeks calculation

  • Strong understanding of factor models, correlation structure, concentration risk, and portfolio attribution

Nice to Have

  • Proficiency in Rust, C++, or other systems languages for performance-critical components

  • Experience with MLOps, model monitoring, and adaptive retraining pipelines for regime detection

  • Background in derivatives pricing, options market making, or volatility arbitrage

  • Familiarity with FIX protocol, Betfair or Matchbook API experience, and ultra-low-latency trading infrastructure

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks. Base salary is one hundred and fifty to two hundred and fifty thousand (plus bonus), depending on experience.