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Quantitative Analytics Jobs in California (NOW HIRING)

Quantitative Developer

San Francisco, CA · On-site

$180K - $280K/yr

Implement, test, and refine models, signals, and analytical workflows. * Maintain a consistent ... quantitative field. Preferred Competencies * Prior full-time experience in finance, data science ...

Implement, test, and refine models, signals, and analytical workflows. * Maintain a consistent ... quantitative field. Preferred Competencies * Prior full‑time experience in finance, data science ...

Showing results 21-40

Quantitative Analytics information

See California salary details

$55.8K

$132.1K

$236.9K

How much do quantitative analytics jobs pay per year?

As of Aug 10, 2026, the average yearly pay for quantitative analytics in California is $132,124.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $143,600.00 per year, depending on experience, location, and employer.

Is quantitative analytics a good career path?

Quantitative analytics is a strong career choice for individuals with skills in mathematics, statistics, and programming, often involving tools like Python, R, or SQL. It offers opportunities in finance, risk management, and data-driven decision making, with roles typically requiring analytical thinking and problem-solving abilities. The field is known for competitive salaries and demand for skilled professionals, especially in finance and technology sectors.

What is a quantitative analyst's salary?

A quantitative analyst's salary typically ranges from $70,000 to over $150,000 annually, depending on experience, location, and industry. Senior roles or those in major financial centers can earn significantly higher, often supplemented with bonuses and incentives. Strong skills in programming, statistics, and financial modeling are highly valued in this field.

What is quantitative analytics?

Quantitative analytics is the practice of using mathematical models, statistical techniques, and computational tools to analyze data and make informed decisions, typically in finance, business, or risk management. Quantitative analysts, often called 'quants,' use these methods to develop trading strategies, assess risk, value financial instruments, and optimize investment portfolios. Their work combines expertise in mathematics, programming, and finance to solve complex problems and provide actionable insights for organizations.

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

To thrive as a Quantitative Analyst, you need strong mathematical, statistical, and programming skills, typically supported by a degree in finance, mathematics, statistics, or a related field. Familiarity with technical tools such as Python, R, MATLAB, SQL, and financial modeling software is commonly required. Analytical thinking, attention to detail, and effective communication help distinguish top performers in this role. These skills and qualities are crucial for developing accurate financial models and providing actionable insights that drive data-informed decision-making.

What is quantitative analytics salary?

The salary for a quantitative analyst typically ranges from $70,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those in financial hubs can earn higher, often exceeding $200,000 with bonuses and incentives. Skills in programming, statistical analysis, and financial modeling are highly valued in this field.

What are some common challenges faced by professionals in quantitative analytics, and how can they be addressed?

Professionals in Quantitative Analytics often face challenges such as managing large and complex data sets, staying updated with rapidly evolving analytical tools, and effectively communicating technical results to non-technical stakeholders. Addressing these challenges involves continual learning, collaborating closely with IT and data engineering teams, and developing strong presentation skills to translate quantitative findings into actionable business insights. Embracing cross-functional teamwork and ongoing professional development can help quantitative analysts thrive in their roles.

What is the difference between Quantitative Analytics vs Data Analyst?

AspectQuantitative AnalyticsData Analyst
Required CredentialsDegree in Mathematics, Statistics, or related fields; often advanced certificationsBachelor's degree in Data Science, Statistics, or related fields; certifications like SQL or Excel skills
Work EnvironmentFinancial firms, investment banks, hedge funds, or tech companies focusing on complex data modelingBusiness, marketing, healthcare, or retail sectors analyzing data trends and reporting
Employer & Industry UsageUsed in finance, trading, risk management, and quantitative researchUsed across various industries for reporting, visualization, and basic data analysis

Quantitative Analysts focus on developing complex mathematical models to inform investment decisions and risk management, often requiring advanced degrees and specialized skills. Data Analysts typically handle data collection, cleaning, and basic analysis to generate reports and insights for business decisions. While both roles work with data, Quantitative Analytics involves more advanced statistical modeling and programming, primarily in finance and tech sectors, whereas Data Analysts focus on descriptive analytics across diverse industries.

What cities in California are hiring for Quantitative Analytics jobs? Cities in California with the most Quantitative Analytics job openings:
Infographic showing various Quantitative Analytics job openings in California as of August 2026, with employment types broken down into 1% Internship, 80% Full Time, 14% Part Time, 2% Temporary, and 3% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $132,124 per year, or $63.5 per hour.

Senior Quantitative Researcher - Risk Modeling

Swish Analytics

San Francisco, CA

Full-time

Re-posted 27 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.