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Data Science And Analytics Jobs in California (NOW HIRING)

Evolver

Applied Data Science Intern

Palo Alto, CA · On-site

Data analysis and machine learning pipelines * AI agents, retrieval systems, and evaluation ... Computer Science * Data Science & Analytics * Applied AI & Machine Learning * Enterprise ...

Evolver

Applied Data Science Intern

Palo Alto, CA

Data analysis and machine learning pipelines * AI agents, retrieval systems, and evaluation ... Computer Science * Data Science & Analytics * Applied AI & Machine Learning * Enterprise ...

eBay Inc.

Data Science - Analyst 4

San Jose, CA · On-site

$149.20 - $199.20/hr

About the team and the role The Shipping Analytics team drives eBay's most important shipping ... Demonstrated success applying data science, optimization, and AI techniques to drive measurable ...

Tiger Analytics

Data Science Leader

California City, CA · On-site

$120 - $160/hr

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for ... Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value ...

Roblox

Principal Data Scientist - Safety

San Mateo, CA · On-site

WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach ...

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Data Science And Analytics information

See California salary details

$37K

$121.1K

$193.9K

How much do data science and analytics jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data science and analytics 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 is data science and analytics?

Data Science and Analytics refer to the fields that focus on extracting meaningful insights from large and complex data sets. Data Science combines statistics, computer science, and domain knowledge to analyze data, build predictive models, and support data-driven decision-making. Analytics, which is a core part of data science, involves examining data to discover trends, patterns, and correlations that can help organizations solve problems or improve processes. Professionals in these fields use tools such as Python, R, SQL, and machine learning algorithms to analyze data and communicate findings to stakeholders.

What are some common challenges faced by data science and analytics professionals when working with cross-functional teams?

Data science and analytics professionals often collaborate with colleagues from diverse backgrounds such as engineering, marketing, and business operations. One common challenge is translating complex analytical findings into actionable insights that non-technical stakeholders can easily understand. Additionally, aligning project objectives and timelines across teams can require strong communication and project management skills. Overcoming these challenges is essential for ensuring that data-driven solutions are effectively implemented and contribute to organizational goals.

What are the key skills and qualifications needed to thrive as a data science and analytics professional, and why are they important?

To thrive in Data Science and Analytics, you need strong skills in statistics, data manipulation, and programming, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools like Python, R, SQL, and data visualization platforms such as Tableau, along with knowledge of machine learning frameworks, is highly valued. Strong problem-solving ability, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills are crucial for turning raw data into strategic decisions that drive organizational success.

What is the difference between Data Science And Analytics vs Data Analysis?

AspectData Science And AnalyticsData Analysis
Required SkillsStatistical modeling, programming, machine learningData cleaning, descriptive statistics, visualization
Work EnvironmentCross-functional teams, R&D, predictive modelingBusiness reporting, dashboards, ad hoc analysis
Tools & TechnologiesPython, R, SQL, Hadoop, SparkExcel, SQL, Tableau, Power BI
Industry UsageTech, finance, healthcare, marketingRetail, finance, healthcare, operations

Data Science And Analytics involves advanced techniques like machine learning and predictive modeling, often requiring programming skills. Data Analysis focuses on interpreting existing data through descriptive statistics and visualization for decision-making. Both roles are essential but differ in complexity and scope.

What can I do with data science and analytics?

Data science and analytics professionals analyze large datasets to extract insights, support decision-making, and improve business processes. They use tools like Python, R, and SQL, and often work in environments that require strong statistical and programming skills. These roles can lead to careers in industries such as finance, healthcare, marketing, and technology, with opportunities for advancement and specialization.

What jobs can I get with a data science and analytics degree?

A degree in data science and analytics can lead to roles such as data analyst, data scientist, business intelligence analyst, machine learning engineer, and data engineer. These positions typically require skills in programming languages like Python or R, data visualization tools, and statistical analysis, often with certifications or experience in big data platforms and SQL. Job responsibilities include interpreting complex data, building predictive models, and supporting data-driven decision-making.

What cities in California are hiring for Data Science And Analytics jobs?

Cities in California with the most Data Science And Analytics job openings:

Data Science And Analytics jobs near you
Infographic showing various Data Science And Analytics job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Applied Data Science Intern

Evolver

Palo Alto, CA • On-site

Full-time, Internship

Re-posted 5 days ago

Job description

Applied Data Science Summer Internship
About Us:
Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In just 1.5 years, the company has grown from 0 to nearly 100 employees, bringing together an exceptional team of technologists, researchers, and industry experts. Founders includes former executives from some of the world's top organizations, including the former Global CTO and Global Board Member of Ernst and Young and the former VP of AI from Microsoft, alongside senior leaders from other major global enterprises. The team includes multiple PhDs and a strong concentration of employees with advanced degrees from leading universities. This in-person internship offers a small cohort of students the opportunity to work directly alongside experienced operators and AI experts while gaining hands-on exposure to using the latest innovations in data science applications at a frontier startup environment.
Program Details:
Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science techniques to enterprise datasets while learning to leverage and deploy AI systems for real-world Fortune 500 business use cases.
This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and enterprise software deployment.
  • Duration: 10 weeks (full-time), June through Early August.
  • Competitive Compensation: Tailored to your experience and skill set.
  • Format: Hybrid (4+ days in person) - Based in Palo Alto, CA off University Ave
  • Cohort Size: Small and mentorship-focused
  • Learning Goals: Develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.

Role Details:
Interns will contribute to real data innovation projects involving:
  • Data analysis and machine learning pipelines
  • AI agents, retrieval systems, and evaluation frameworks
  • Enterprise AI integration and deployment tooling
  • Product prototyping and applied research
  • Automation systems for large-scale organizational use
  • Real world enterprise use cases of graph theory
  • Gain direct exposure to Fortune 500 clients
  • Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.

Projects are oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.
Mentorship & Learning
Interns will work closely with experienced staff and technical mentors with expertise in:
  • Computer Science
  • Data Science & Analytics
  • Applied AI & Machine Learning
  • Enterprise Infrastructure
  • Scalable AI Deployment
  • Risk and Compliance Frameworks
  • Tax and Audit

The program is structured as a high-engagement cohort-based apprenticeship experience emphasizing:
  • Daily in person technical collaboration
  • Rapid learning and iteration
  • Exposure to real deployment challenges
  • Cross-disciplinary problem solving
  • Professional development in AI engineering and enterprise systems

Who Should Apply:
We welcome applications from:
  • Graduate students with a record of excellence
  • Exceptional advanced undergraduates

All candidates are required to be recommended by an accredited professor leading a relevant program at a top university. Will be verified during application process.
Strong candidates typically demonstrate:
  • Programming experience
  • Curiosity about AI systems and emerging technologies
  • Initiative, creativity, and strong problem-solving ability
  • Prior technical, research, or project experience

You do not need deep expertise in every area, we value intellectual curiosity, adaptability, and motivation to build.

Apply