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Junior Quantitative Developer Jobs in California

... 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 ...

Data Science and Data Engineering Job Qualifications: Skills: Analytics, Datasource, Data ... EDUCATION: Bachelor's degree with one to two (1-2) years' experience in quantitative science ...

Senior Software Developer

Newport Beach, CA

$58.50 - $77.50/hr

The solution leverages cutting-edge techniques to empower Portfolio Managers and Quant Research ... Mentor junior team members and perform code reviews to maintain high-quality standards.

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Junior Quantitative Developer information

See California salary details

$23.7K

$87.8K

$135.7K

How much do junior quantitative developer jobs pay per year?

As of Jul 28, 2026, the average yearly pay for junior quantitative developer in California is $87,810.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,100.00 and $85,900.00 per year, depending on experience, location, and employer.

What is a Junior Quantitative Developer job?

A Junior Quantitative Developer is responsible for developing, implementing, and maintaining quantitative models and tools used in trading, risk management, or financial analysis. They work closely with quantitative analysts and traders to optimize algorithms, improve performance, and ensure data accuracy. This role typically requires strong programming skills in languages like Python, C++, or Java, along with a solid understanding of mathematics, statistics, and financial markets. Junior Quantitative Developers often contribute to backtesting trading strategies, optimizing execution algorithms, and improving financial models. The position serves as a foundational step for a career in quantitative finance, providing hands-on experience in both development and financial modeling.

What are typical daily responsibilities for a Junior Quantitative Developer?

As a Junior Quantitative Developer, your daily tasks often include writing and optimizing code to implement quantitative models, analyzing large datasets, and performing model validation or back-testing. You’ll also collaborate closely with senior quants, traders, and software engineers to refine strategies or troubleshoot issues as they arise. Additionally, you may maintain documentation, participate in code reviews, and stay updated with the latest development practices and financial concepts. This role offers a dynamic experience that builds both your technical programming skills and your understanding of financial markets.

What are the key skills and qualifications needed to thrive in the Junior Quantitative Developer position, and why are they important?

To thrive as a Junior Quantitative Developer, you need a solid background in mathematics, statistics, and programming—often supported by a relevant degree in fields like computer science, engineering, or quantitative finance. Familiarity with programming languages such as Python, C++, or R, as well as experience using version control systems and exposure to financial data platforms, is highly valuable. Attention to detail, strong analytical thinking, and effective collaboration skills help you excel in dynamic, team-based environments. These capabilities are essential for developing and maintaining quantitative models that support data-driven decision-making in finance or related sectors.

What are the most commonly searched types of Quantitative Developer jobs in California? The most popular types of Quantitative Developer jobs in California are:
What job categories do people searching Junior Quantitative Developer jobs in California look for? The top searched job categories for Junior Quantitative Developer jobs in California are:
What cities in California are hiring for Junior Quantitative Developer jobs? Cities in California with the most Junior Quantitative Developer job openings:
Infographic showing various Junior Quantitative Developer job openings in California as of July 2026, with employment types broken down into 82% Full Time, 6% Part Time, 1% Temporary, and 11% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $87,810 per year, or $42.2 per hour.
Senior Quantitative Researcher - Risk Modeling

Senior Quantitative Researcher - Risk Modeling

Swish Analytics

San Francisco, CA

Full-time

Posted 14 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.