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Research Python Jobs in California (NOW HIRING)

Python Developer

San Francisco, CA · On-site

$140K - $175K/yr

We are seeking an experienced Python Developer to join our team supporting the front office. The ... This role supports a broad set of stakeholders including equity & fixed income research, trading ...

Python Developer

San Jose, CA · On-site

$59 - $81.25/hr

As a Python Developer, you will play a key role in developing secure, scalable, and production ... and research services. Founded in 2003, the company is headquartered in Pittsburgh, USA, with a ...

Python Software Engineer Location : Fremont, CA (Only Local Candidates Onsite) Where you ll work ... Passion for writing clean, modular, and sustainable code to transition research into production

New

Python Developer

Fremont, CA · On-site

$55 - $75.75/hr

Python Developer Job Location: Fremont, CA | Onsite 5 days a week Description: AgreeYa is a global ... Research. * Experience building and deploying AI solutions in cloud or large-scale production ...

Lead Python Developer

San Jose, CA · On-site

$164K - $201K/yr

Lead Python Developer Location San Jose, CA/ Research Triangle Park, NC Remote for till July then onsite Duration: 6+ Months C2C / C2H / Fulltime Detailed * Tech Lead * Strong tech lead experience

We offer a survey data analysis platform that allows market researchers, analysts, and marketers to ... We are hiring a Python Software Systems Engineer to help develop and deploy our platform. We are ...

Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc ... Deep technical knowledge, and research experience in deep learning, reinforcement and/or imitation ...

We apply deep learning research to large scale EEG datasets collected on affordable hardware to ... Strong programming skills in Python with ability to quickly learn new frameworks * Solid ...

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Showing results 1-20

Research Python information

What is a Research Python Developer?

A Research Python Developer is a professional who uses the Python programming language to support and conduct research activities. They often work with data analysis, machine learning, simulation, and automation to solve scientific or academic problems. Their role may involve developing prototypes, processing large datasets, and collaborating with researchers to implement algorithms or models. Research Python Developers are commonly found in universities, research institutions, and tech companies focused on innovation.

Is Python good for research?

Research Python developers use Python because of its simplicity, extensive libraries, and strong support for data analysis, machine learning, and scientific computing. It is widely adopted in academia and industry for research projects, often complemented by tools like Jupyter notebooks and frameworks such as NumPy and pandas.

What Python jobs are in demand?

Python development roles such as data scientist, machine learning engineer, backend developer, and automation engineer are currently in high demand. These positions often require knowledge of frameworks like Django or Flask, data analysis libraries, and proficiency in cloud platforms. Demand is driven by industries including technology, finance, healthcare, and e-commerce, with many roles requiring strong problem-solving skills and experience with version control tools like Git.

Will AI replace Python coders?

Research Python coders develop and maintain Python-based applications and tools, and while AI can automate certain coding tasks, it is unlikely to fully replace human programmers due to the need for problem-solving, creativity, and understanding complex requirements. AI tools can assist coders by increasing efficiency and handling repetitive tasks, but human oversight remains essential for quality and innovation.

What is the difference between Research Python vs Data Analyst?

AspectResearch PythonData Analyst
Required SkillsPython programming, research methodologies, data analysisData analysis, visualization, SQL, Excel
Work EnvironmentResearch labs, academic institutions, tech companiesBusiness settings, corporate offices, consulting firms
Common CertificationsPython certifications, research methodology coursesMicrosoft Excel, Tableau, SQL certifications
Industry UsageAcademic research, scientific projects, tech R&DBusiness intelligence, marketing, finance

Research Python focuses on using Python for scientific and academic research, emphasizing programming and research methodologies. Data Analysts primarily analyze and interpret data to support business decisions, often using tools like Excel and Tableau. While both roles require data skills, Research Python is more technical and research-oriented, whereas Data Analysts focus on data interpretation within business contexts.

What are the key skills and qualifications needed to thrive as a Research Python Developer, and why are they important?

To thrive as a Research Python Developer, you need expertise in Python programming, data analysis, and a strong foundation in mathematics or computer science, often supported by an advanced degree. Familiarity with libraries such as NumPy, pandas, TensorFlow, and version control systems like Git is typically required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for translating research goals into practical code. These skills are essential for developing robust research solutions, collaborating with interdisciplinary teams, and advancing scientific or technical projects.

What are some common challenges faced by Research Python Developers when collaborating with cross-functional teams?

Research Python Developers often work alongside data scientists, domain experts, and engineers, which can present challenges such as aligning on project goals, translating research requirements into efficient code, and ensuring reproducibility of results. Effective communication and thorough documentation are key to overcoming these challenges. Additionally, Research Python Developers may need to adapt their code to integrate with different tools or platforms used by other team members, requiring flexibility and a willingness to learn new technical concepts.

Is Python still in demand in 2026?

Python remains a highly in-demand skill for research roles, including those involving data analysis, machine learning, and automation. Its versatility, extensive libraries, and widespread use in industry and academia ensure continued demand for professionals proficient in Python in 2026.
What cities in California are hiring for Research Python jobs? Cities in California with the most Research Python job openings:
Python Developer

Python Developer

Cirrus Group Consulting

San Francisco, CA • On-site

$140K - $175K/yr

Full-time

Posted 22 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.