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Data Science Apprentice Jobs in California (NOW HIRING)

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Data Science Apprentice information

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How much do data science apprentice jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for data science apprentice in California is $22.51, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $24.90 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Apprentice, and why are they important?

To thrive as a Data Science Apprentice, you need a solid understanding of statistics, programming (often Python or R), and foundational knowledge in data analysis, usually supported by relevant coursework or a degree in a related field. Familiarity with data visualization tools (such as Tableau or Power BI), SQL databases, and machine learning libraries is commonly expected. Curiosity, problem-solving ability, and effective communication help apprentices stand out by enabling them to learn quickly and convey complex findings clearly. Mastering these skills ensures you can contribute to data-driven projects and grow into more advanced roles in the field.

What is a Data Science Apprentice?

A Data Science Apprentice is an entry-level professional who is learning the skills required to become a data scientist, often through a structured apprenticeship program. They work under the guidance of experienced data scientists to gain hands-on experience in analyzing data, building models, and using data science tools and techniques. Apprenticeships typically combine on-the-job training with classroom instruction, allowing apprentices to develop both practical and theoretical knowledge. The goal is to prepare apprentices for a full-time role in data science by the end of the program.

How do Data Science Apprentices typically collaborate with senior data scientists and other departments?

As a Data Science Apprentice, you'll often work closely with senior data scientists through mentorship and project-based tasks. Collaboration usually involves assisting with data cleaning, exploratory analysis, and supporting model development under supervision. You'll also interact with team members from engineering, product, or business departments to understand project goals and present findings. This cross-functional teamwork helps you build both technical and communication skills, preparing you for more independent roles in the future.
What are the most commonly searched types of Data Science jobs in California? The most popular types of Data Science jobs in California are:
What are popular job titles related to Data Science Apprentice jobs in California? For Data Science Apprentice jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Apprentice jobs in California look for? The top searched job categories for Data Science Apprentice jobs in California are:
What cities in California are hiring for Data Science Apprentice jobs? Cities in California with the most Data Science Apprentice job openings:
Infographic showing various Data Science Apprentice job openings in California as of June 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 100% In-person job distribution, with an average salary of $46,828 per year, or $22.5 per hour.

AI Agent Software Engineer

Cooperidge Consulting Firm

San Francisco, CA โ€ข On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago


Job description

Cooperidge Consulting Firm is seeking an AI Agent Software Engineer for a high-momentum AI platform leader in San Francisco, CA.

This is a full-cycle ownership role for engineers who want to move beyond "opaque prompts" and build production-ready, autonomous agents. You will design AI systems that handle high-sensitivity tasks-such as password resets and complex account resolutions-traditionally managed by human teams in finance and healthcare. Utilizing a proprietary logic framework and real-time observability tools, you will build agents that are transparent, auditable, and capable of end-to-end issue resolution. This is an elite opportunity for a systems-minded engineer to join an engineer-led culture where "no prior AI experience" is required-only a mastery of robust software engineering and deep curiosity.
Job Responsibilities

  • Autonomous Agent Design: Build AI-driven voice and chat agents that anticipate customer intent and resolve complex workflows end-to-end.
  • Logic Framework Implementation: Translate natural language instructions into structured, modular, and auditable workflows using a proprietary agent logic framework.
  • Observability & Tracing: Use real-time tools to trace agent decisions, ensuring every action is understandable, debuggable, and continuously improving.
  • Performance Engineering: Analyze large-scale performance data to identify behavioral trends and drive platform-wide improvements in agent reasoning.
  • Model Integration: Experiment with and tune the latest voice and language models for enterprise-grade reliability, low latency, and broad language coverage.
  • Full-Cycle Ownership: Take agent concepts from initial design and prototyping through to production deployment and rapid iteration.
  • Cross-Functional Partnership: Collaborate with product and operations teams to identify friction points and deliver measurable improvements to the customer experience.

Requirements

Technical Core
  • Minimum of 2+ years of professional experience building production-grade software systems for real users.
  • Language Mastery: Strong proficiency in Python and TypeScript, with expertise in asynchronous programming and error handling.
  • Systems Expert: Excellent debugging skills using profilers, log aggregators, and raw data analysis to troubleshoot complex distributed systems.
  • Computer Science Foundation: Strong background in CS fundamentals; while specific language experience is flexible, a deep understanding of performance optimization is required.
Mindset & Curiosity
  • The "AI Apprentice" Mindset: No prior AI experience is required; the team will provide comprehensive training on agentic reasoning and LLM integration.
  • Proactive Reasoning: A deep curiosity about how AI agents reason, why they fail, and how to make them more reliable.
  • Obsession with UX: A focus on building robust, transparent systems that solve real human problems.
Plus Factors
  • Exposure to multimodal AI or voice interface development.
  • Experience with conversational automation frameworks or enterprise CX platforms.

Benefits

  • Comprehensive health, vision, and dental insurance plans
  • Life insurance coverage
  • 401(k) retirement plan with company matching contributions
  • Paid time off including vacation, sick leave, and holidays
  • Opportunities for career growth and advancement