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Python Quantitative Algorithmic Trading Jobs in California

Triumph Arcade, Inc

Quant Strategist

San Francisco, CA · On-site

$200K - $400K/yr

Develop and optimize core risk-taking and revenue-generating algorithms - the pricing engines ... Prior experience as a quantitative trader or quantitative researcher. * Experience in competitive ...

Triumph

Quant Strategist

San Francisco, CA · On-site

$200K - $400K/yr

Develop and optimize core risk-taking and revenue-generating algorithms -- the pricing engines ... Prior experience as a quantitative trader or quantitative researcher. * Experience in competitive ...

Hudson River Trading

Research Engineer

London, CA

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological ... Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit ...

Poesis

Quantitative Developer

San Francisco, CA · On-site

$180K - $280K/yr

... trading strategies * Strong Python skills (pandas, numpy, scipy, matplotlib); comfort with SQL ... quantitative field. Preferred Competencies * Prior full-time experience in finance, data science ...

Jobtailor

Quantitative Developer

San Francisco, CA · On-site

$180 - $280/hr

... trading strategies * Strong Python skills (pandas, numpy, scipy, matplotlib); comfort with SQL ... quantitative field. Preferred Competencies * Prior full‑time experience in finance, data science ...

BlackRock

Quant Research, Associate

San Francisco, CA

... quantitative investors of many different backgrounds. * A passion for algorithmic development and ... Excellent knowledge of Python / Pandas, as well as Java or C/C++. * Well-rounded proficiency with ...

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All JobsPython Quantitative Algorithmic Trading JobsPython Quantitative Algorithmic Trading Jobs in California

Python Quantitative Algorithmic Trading information

See California salary details

$96.7K

$167.5K

$256.1K

How much do python quantitative algorithmic trading jobs pay per year?

As of Aug 11, 2026, the average yearly pay for python quantitative algorithmic trading in California is $167,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,700.00 and $196,400.00 per year, depending on experience, location, and employer.

What is the difference between Python Quantitative Algorithmic Trading vs Python Quantitative Trading Analyst?

AspectPython Quantitative Algorithmic TradingPython Quantitative Trading Analyst
CredentialsDegree in Computer Science, Finance, or related fields; coding certificationsDegree in Finance, Economics, or related fields; strong analytical skills
Work EnvironmentDeveloping algorithms, coding, backtesting strategiesAnalyzing market data, supporting trading strategies, reporting
Industry UsageFinancial firms, hedge funds, proprietary trading firmsAsset management firms, trading desks, financial institutions

Python Quantitative Algorithmic Traders focus on designing and implementing automated trading algorithms using programming skills, while Python Quantitative Trading Analysts analyze data and support trading strategies without necessarily coding the algorithms themselves. Both roles require strong quantitative skills and familiarity with Python, but their daily tasks and responsibilities differ significantly.

What are the key skills and qualifications needed to thrive as a Python quantitative algorithmic trader?

To thrive as a Python Quantitative Algorithmic Trader, you need strong quantitative analysis, programming expertise (especially in Python), and a solid background in mathematics, statistics, or finance, often supported by a relevant degree. Familiarity with financial data platforms, algorithmic trading systems, and libraries such as pandas, NumPy, and scikit-learn, as well as experience with backtesting frameworks, is essential. Critical thinking, attention to detail, and effective communication help you interpret data, manage risk, and collaborate with team members. These skills ensure effective strategy development, implementation, and adaptation in fast-moving financial markets.

What are some common challenges faced by Python quantitative algorithmic traders, and how can job seekers prepare to overcome them?

Python quantitative algorithmic traders often face challenges such as rapidly changing market conditions, ensuring code efficiency for low-latency execution, and maintaining data integrity across large datasets. Additionally, traders must continuously backtest strategies to avoid overfitting and adapt to evolving regulatory requirements. To prepare, job seekers should strengthen their coding skills with a focus on performance optimization, familiarize themselves with financial data handling, and stay current with industry best practices in both technology and trading strategy development.

What is Python quantitative algorithmic trading?

Python Quantitative Algorithmic Trading refers to the use of Python programming to develop, test, and implement mathematical models and automated strategies for trading financial instruments. Professionals in this field use quantitative analysis, statistical techniques, and historical data to create algorithms that can execute trades on financial markets without human intervention. Python is widely favored due to its robust libraries, ease of use, and strong community support, making it ideal for handling large datasets and rapid prototyping of trading strategies.
What are popular job titles related to Python Quantitative Algorithmic Trading jobs in California? For Python Quantitative Algorithmic Trading jobs in California, the most frequently searched job titles are:
What job categories do people searching Python Quantitative Algorithmic Trading jobs in California look for? The top searched job categories for Python Quantitative Algorithmic Trading jobs in California are:
What cities in California are hiring for Python Quantitative Algorithmic Trading jobs? Cities in California with the most Python Quantitative Algorithmic Trading job openings:
Python Quantitative Algorithmic Trading jobs near you
Infographic showing various Python Quantitative Algorithmic Trading job openings in California as of August 2026, with employment types broken down into 2% Internship, 85% Full Time, 5% Part Time, 2% Temporary, and 6% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $167,506 per year, or $80.5 per hour.

Quant Strategist

Triumph Arcade, Inc

San Francisco, CA • On-site

$200K - $400K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted yesterday

Job description

The Role
As a Quant Strategist, you'll sit at the intersection of mathematics, computer science, and core business decisions. You'll have a direct impact on all facets of the business, applying your quantitative rigor directly to what drives revenue and player experience. You'll build the models and frameworks that power our most critical business decisions.
You'd be joining a small, high-output quant team (4 people today) that operates more like a trading desk than a data org. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems.
The team is led by a former quant trader, and current members left careers in quantitative trading to be here. The problems are as deep and interesting as what you'd find at a quant fund - constrained optimization, adversarial dynamics, real-money risk - but with more ownership, faster feedback loops, and direct impact on what gets built. You ship something, and you see it in the numbers the next day.
What You'll Do
  • Develop and optimize core risk-taking and revenue-generating algorithms - the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's business.
  • Own the quantitative framework for Rips by Triumph: pricing models, pack economics, and rarity calibration.
  • Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology.
  • Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.
  • Partner closely with engineering, product, and leadership to translate model outputs into real-time production systems and strategic decisions.
  • Design and build machine learning models that directly inform acquisition spend and product decisions.

Qualifications
  • Bachelor's degree in a quantitative subject: math, physics, computer science, data science, or a related discipline.
  • True depth and mastery over any quantitative domain: probability, statistics, applied machine learning, computer science, or math. We want spiky people who are confident that they are the best in their discipline.
  • Proficiency in Python and SQL.
  • Experience working with large amounts of data.

Preferred
  • Prior experience as a quantitative trader or quantitative researcher.
  • Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.
  • Nationally competitive in any activity. Some members from our company include national champions in debate, Clash Royale, and Poker.

Why Triumph?
  • High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.
  • High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.
  • High energy. Passionate team who are proud of our work and velocity (16x year over year growth).
  • Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.

Our team gathers 5 days a week at Triumph's headquarters at Levi's Plazain San Francisco.

Apply