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Python Financial Jobs in California (NOW HIRING)

... Financial Industry. Qualifications : Required : • Python • AWS • SQL • Very strong hands-on experience in Python data engineering processing, Data processing development project. • Must ...

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

We are a lean, mission-driven team passionate about the positive impact community financial institutions have on the people they serve. The Role We're looking for a Python Integrations Developer to ...

We are a lean, mission-driven team passionate about the positive impact community financial institutions have on the people they serve. The Role We're looking for a Python Integrations Developer to ...

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

We are a lean, mission-driven team passionate about the positive impact community financial institutions have on the people they serve. The Role We're looking for a Python Integrations Developer to ...

Helping the customers and businesses we serve to make better and smarter financial decisions and ... We are seeking a Python developer / solutions architect to drive forward our next-gen model ...

Credit Risk Python Architect

Irvine, CA · On-site

$111K - $131K/yr

Helping the customers and businesses we serve to make better and smarter financial decisions and ... We are seeking a Python developer / solutions architect to drive forward our next-gen model ...

Helping the customers and businesses we serve to make better and smarter financial decisions and ... We are seeking a Python developer / solutions architect to drive forward our next-gen model ...

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Python Financial information

See California salary details

$13

$57

$85

How much do python financial jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for python financial in California is $57.85, according to ZipRecruiter salary data. Most workers in this role earn between $47.69 and $65.72 per hour, depending on experience, location, and employer.

What are some common projects or tasks Python Financial professionals work on in a typical week?

Python Financial professionals commonly work on building and maintaining financial models, analyzing large datasets for trends or anomalies, and automating data collection and reporting processes. They often collaborate with other analysts and finance teams to develop tools that improve efficiency or support investment decisions. Additionally, they may create data visualizations, backtest trading algorithms, and present findings to stakeholders. The work is typically fast-paced and project-driven, offering opportunities to contribute directly to financial strategy and performance.

What is a Python Financial job?

A Python Financial job involves using Python programming to analyze financial data, develop trading algorithms, automate financial processes, or build risk models. Professionals in this role may work in banking, fintech, investment firms, or insurance, leveraging Python libraries like Pandas, NumPy, and Scikit-learn for data analysis and machine learning. These roles often require knowledge of financial markets, quantitative analysis, and data processing to optimize decision-making and strategy development.

What are the key skills and qualifications needed to thrive in the Python Financial position, and why are they important?

To thrive as a Python Financial professional, you need strong programming skills in Python, a background in finance or quantitative analysis, and experience with data analysis and modeling. Familiarity with libraries such as pandas, NumPy, and financial data APIs, along with knowledge of tools like Jupyter notebooks and relevant certifications (e.g., CFA or Financial Risk Manager), is important. Attention to detail, analytical thinking, and the ability to communicate complex findings clearly are valuable soft skills in this role. These competencies enable individuals to extract insights from data, automate financial processes, and support effective business decision-making.

What are the most commonly searched types of Python Financial jobs in California? The most popular types of Python Financial jobs in California are:
What job categories do people searching Python Financial jobs in California look for? The top searched job categories for Python Financial jobs in California are:
What cities in California are hiring for Python Financial jobs? Cities in California with the most Python Financial job openings:
Infographic showing various Python Financial job openings in California as of July 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $120,336 per year, or $57.9 per hour.
Python Developer

Python Developer

Cirrus Group Consulting

San Francisco, CA • On-site

$140K - $175K/yr

Full-time

Re-posted 18 days ago


Job description

We are seeking an experienced Python Developer to join our team supporting the front office. The ideal candidate will have at least 5 years of experience designing, developing, and deploying Python-based solutions in a financial services or investment management environment. This role supports a broad set of stakeholders including equity & fixed income research, trading, and quantitative teams, requiring the ability to work across varying levels of technical maturity. This role also requires participation in the firm’s growing AI initiatives, including governance and integration of AI processes. The individual will collaborate closely with front office teams and Investment Technology leadership to deliver scalable, well-governed Python solutions that support investment decision-making.

 

Key Responsibilities:


•      Design, develop, and maintain Python-based tools and pipelines to support front office investment teams.

•      Develop, maintain, and govern shared data patterns across multiple databases, environments, and other enterprise sources.

•      Support the firm’s cloud migration, including integration of Snowflake and support of Python UDFs.

•      Build and support interactive tools using Plotly and Dash for business users.

•      Establish and maintain internal Python package structures, dependency management standards, and environment reproducibility practices.

•      Implement data quality validation and testing frameworks for data pipelines.

•      Support AI enablement initiatives including LLM integration, governance frameworks, and review of AI-generated code for production readiness.

 

Key Priorities/Deliverables:


•      Implement an internal Python package architecture that enables shared utilities across teams.

•      Establish environment reproducibility and dependency management standards across development and production environments.

•      Define and document Snowflake-Python integration patterns, including reference implementations for data extraction, analytics, and model scoring

•      Establish initial AI governance guardrails including approved model access, data classification for API usage, and review processes for AI-assisted development.

•      Provide mentoring, code review, and documentation to support Python adoption across teams.


Basic Qualifications:


•      5 years of hands-on experience developing in Python

•      5 years of demonstrated production deployment & environment management experience.

•      5 years of experience integrating Python with enterprise data sources, including Snowflake, SQL Server, and REST APIs.

•      5 years of experience building interactive dashboards and visualizations with Plotly and Dash.

•      Bachelor’s degree in Computer Science, Engineering, Mathematics, Finance, or a related field.

 

Preferred Qualifications:


•      Experience designing scalable internal Python architectures in organizations with multiple teams.

•      Hands-on involvement with AI/LLM enablement in an enterprise context, including integration patterns (MCP, API abstraction layers), data governance, and prompt management.

•      Prior experience in asset management or investment research, with working knowledge of portfolio analytics, factor construction, and valuation metrics.

•      Demonstrated ability to design Python package structures and manage dependencies across teams and environments.

•      High attention to detail, particularly around numerical accuracy, and data quality in a financial context.

•      Strong proficiency with pandas, vectorized operations, and data quality handling.

•      Strong communication and stakeholder management skills, with the ability to work directly with non-technical front office users.

•      Proficiency with version control (Git) and collaborative development practices including code review.