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Data Science Machine Learning Jobs in Santa Clara, CA

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Applies data science, machine learning and other analytical modeling methods to develop defensible and reproducible predictive models * Serves as the technical lead for the development of computer ...

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All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Santa Clara, CA

Data Science Machine Learning information

See Santa Clara, CA salary details

$44.3K

$145K

$232.1K

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

As of Sep 2, 2026, the average yearly pay for data science machine learning in Santa Clara, CA is $144,951.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,300.00 and $160,600.00 per year, depending on experience, location, and employer.

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 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.

Is data science machine learning a high paying job?

Data science and machine learning roles are generally high-paying within the tech industry due to the specialized skills required, such as programming, statistical analysis, and experience with tools like Python or TensorFlow. Salaries vary based on experience, location, and company size but tend to be above average compared to many other professions.

What cities near Santa Clara, CA are hiring for Data Science Machine Learning jobs?

Cities near Santa Clara, CA with the most Data Science Machine Learning job openings:

Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 1% Temporary, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $144,149 per year, or $69.3 per hour.

Data Scientist, Senior Enterprise DS & AI Org - Only W2

Rootshell Enterprise Technologies Inc.

Santa Clara, CA • Remote

Other

Re-posted 14 days ago

Job description

Hello All,

Greetings from Rootshell Inc.

Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US. We are actively seeking Data Scientist, Senior-Enterprise DS & AI Org for one of our client, Please share your resume with current location & full contact info

Role: Data Scientist, Senior-Enterprise DS & AI Org

Location: Remote

Only W2

Job Summary:

Notes: Computer vison model experience a must. We will require detail writeup on experience with computer Vison Model.

Key points

  • Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. Demonstrated ability to explain in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
  • Competency in the mathematical and statistical fields that underpin data science
  • Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies
  • Strong in Python & R

Education Minimum: Bachelor's degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.

Education Desired: Master's degree in one of the above areas.

Experience Minimum: 4 years in data science (or 2 years, if possess master's degree, as described above).

Knowledge, Skills, Abilities and (Technical) Competencies:

Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them

Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment

Competency in commonly used data science and/or operations research programming languages, packages, and tools.

Hands-on and theoretical experience of data science/machine learning models and algorithms

Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. Demonstrated ability to explain in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.

Competency in the mathematical and statistical fields that underpin data science

Mastery in systems thinking and structuring complex problems

Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies

Desired: experience building computer vision models

Desired: experience with AWS technologies (S3, GroundTruth, Sagemaker)

With regards

Naveen | Talent Acquisition

Rootshell Enterprise Technologies Inc.

Naveen@rootshellinc.com | www.rootshellinc.com