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Data Science Machine Learning Jobs in California

Your expertise in data analysis, machine learning, and statistical modeling will enable you to ... Stay updated on industry trends and best practices regarding data science methodologies and ...

Data Scientist, Staff

San Diego, CA · On-site

$142.10 - $213.10/hr

Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field. * 5+ years of Data Science or related work experience. * Completed advanced degrees ...

Senior, Data Scientist

San Bruno, CA · On-site

$117K - $234K/yr

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful ...

Showing results 21-40

Data Science Machine Learning information

See California salary details

$37K

$121.1K

$193.9K

How much do data science machine learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for data science machine learning in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data science machine learning professional?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a data science machine learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.
What cities in California are hiring for Data Science Machine Learning jobs? Cities in California with the most Data Science Machine Learning job openings:
Infographic showing various Data Science Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Machine Learning Engineer - People Analytics

Apple Inc.

Cupertino, CA • On-site

$181.10 - $272.10/hr

Other

Medical, Dental, Retirement

Posted 7 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Cupertino, California, United States Corporate Functions

At Apple, our greatest resource is our people, and the People Analytics Team is dedicated to ensuring Apple’s employees are able to do the best work of their lives. Our team is looking for a Machine Learning Engineer who is passionate about crafting, implementing, and operating analytical and machine learning solutions that have direct and measurable impact to Apple and its employees. As a Machine Learning Engineer on Apple's People Analytics Team, you will employ predictive modeling, statistical analysis, and advanced analytical techniques to support solutions for talent management, employee surveys, compensation, and recruiting. Apple's dedication to privacy, the human‑centric nature of our work, and the scale of our business present exciting challenges to traditional machine learning and data science methods. On this team, you will push the limits of existing approaches while delivering tangible business value.

Description

As a Machine Learning Engineer on our team you will engage with our business partners to understand their problems, design data‑driven solutions, and produce proof‑of‑concept and prototype solutions. You will collaborate with data engineers and system architects to implement these solutions in a production environment, and be responsible for the ongoing analytic operation of these solutions.

Responsibilities
  • Design data science / machine learning approaches, applying tried‑and‑true techniques or developing custom algorithms as needed by the business problem.
  • Collaborate with data engineers and platform architects to implement real‑time and batch decisioning solutions in production.
  • Ensure operational and business metric health by monitoring production decision points.
  • Develop metrics to measure performance of analytics solutions, and regularly communicate results to business partners and executives.
  • Research new technologies and methods across machine learning, data engineering, and data visualization to improve the technical capabilities of the team.
Minimum Qualifications
  • MS with 5+ years of professional experience applying data science to real‑world business problems
  • Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection
  • Proficiency in writing SQL queries involving database joins and analytical/window functions
  • Ability to implement data science pipelines, analyses, and applications in a programming language such as Python or R
  • Prior experience working with employee data or HR systems
  • Experience with natural language processing (sentiment, topic identification, summarization, entity extraction) and network analysis a plus.
  • Ability to translate business processes and data into an analytic solution.
  • Ability to comprehend and debug complex systems integrations spanning multiple toolchains and teams
  • Ability to extract meaningful business insights from data and identify the stories behind the patterns
  • Excellent presentation skills, distilling complex analysis and concepts into concise business‑focused takeaways
  • Creativity to engineer novel features and signals, and to push beyond current tools and approaches
Preferred Qualifications
  • Ph.D. in I-O Psychology, Economics, Operations Research, Computer Science, or Statistics with a data science fellowship or prior professional experience as a data scientist
  • Experience working with employee data or HR systems

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Benefits
  • Comprehensive medical and dental coverage
  • Retirement benefits
  • A range of discounted products and free services
  • Reimbursement for educational expenses (including tuition)
  • Discretionary bonuses or commission payments
  • Relocation assistance

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976