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Data Science Analytics Jobs in California (NOW HIRING)

eBay

Data Science - Analyst 4

San Jose, CA · On-site

The role involves leveraging data-driven insights and advanced analytics to improve shipping ... Required : • Bachelor's degree in Engineering, Computer Science, Economics, Statistics ...

Five9

Vice President, Data Science

San Ramon, CA · On-site

Applied Data Science & Analytics * Strong proficiency in statistical analysis, A/B experimentation ... causal inference, and performance measurement. * Demonstrated success turning data insights into ...

Apple

Sr. Data Science Leader - iCloud

Cupertino, CA · On-site

$83 - $111/hr

Description The Sr. Data Science Leader will oversee and grow a team of senior data scientists and managers responsible for analytics, experimentation, modeling, and data-driven insights that ...

Apple

App Store Data Scientist

Cupertino, CA · On-site

Minimum Qualifications 5+ years of professional experience in data science, machine learning, or digital product analytics Mastery in SQL-based languages, and proficiency large-scale data languages ...

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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All JobsData Science Analytics JobsData Science Analytics Jobs in California

Data Science Analytics information

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$24

$54

$93

How much do data science analytics jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for data science analytics in California is $54.03, according to ZipRecruiter salary data. Most workers in this role earn between $43.41 and $61.20 per hour, depending on experience, location, and employer.

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

To thrive in Data Science Analytics, a strong background in statistics, data modeling, and programming (often with a degree in computer science, mathematics, or a related field) is essential. Familiarity with tools such as Python, R, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of machine learning libraries, is typically required. Critical thinking, problem-solving, and effective communication skills help professionals translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful information from data and driving informed decision-making within organizations.

How do data science analytics professionals typically collaborate with other departments within an organization?

Data science analytics professionals often work closely with teams across the organization, such as marketing, finance, product development, and IT. Their role involves understanding business needs, gathering requirements, and translating complex data findings into actionable insights for non-technical stakeholders. Effective communication and teamwork are essential, as data scientists may participate in cross-functional meetings, present their analyses, and tailor their recommendations to support strategic decision-making. This collaborative approach not only enhances the impact of analytics projects but also fosters continuous learning and innovation within the organization.

What is the difference between Data Science Analytics vs Data Analyst?

AspectData Science AnalyticsData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; programming skillsDegree in Statistics, Mathematics, or related fields; proficiency in Excel and SQL
Work EnvironmentOften involves complex modeling, machine learning, and predictive analyticsFocuses on data cleaning, reporting, and visualization
Employer & Industry UsageTech companies, finance, healthcare, and research institutionsBusiness, marketing, finance, and operations across various industries

Data Science Analytics and Data Analysts both work with data, but Data Science Analytics typically involves advanced modeling and predictive techniques, while Data Analysts focus on data reporting and visualization. The roles often overlap, but Data Science Analytics requires more technical skills and a deeper understanding of algorithms.

What is data science analytics?

Data science analytics is the process of extracting insights and knowledge from data using statistical, mathematical, and computational techniques. It involves collecting, cleaning, analyzing, and visualizing data to help organizations make informed decisions. Professionals in this field use tools like Python, R, and SQL to interpret complex data sets, build predictive models, and identify trends or patterns. Data science analytics plays a key role in industries such as finance, healthcare, retail, and technology, enabling businesses to optimize operations and improve outcomes.
What are the most commonly searched types of Data Science Analytics jobs in California? The most popular types of Data Science Analytics jobs in California are:
What are popular job titles related to Data Science Analytics jobs in California? For Data Science Analytics jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Analytics jobs in California look for? The top searched job categories for Data Science Analytics jobs in California are:
What cities in California are hiring for Data Science Analytics jobs? Cities in California with the most Data Science Analytics job openings:
Data Science Analytics jobs near you
Infographic showing various Data Science Analytics job openings in California as of July 2026, with employment types broken down into 1% Internship, 91% Full Time, 5% Part Time, 1% Temporary, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $112,382 per year, or $54 per hour.
Director, Data Science - GTM (Data, Analytics & AI)

Director, Data Science - GTM (Data, Analytics & AI)

Snowflake

Menlo Park, CA • On-site

$262K - $376K/yr

Full-time

Re-posted 2 days ago

Job description

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset - who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
About the Role
We are seeking a Director of Data Science to lead high-impact analytics and AI initiatives across Snowflake's Go-To-Market organization. This role sits within the Data, Analytics & AI (DAA) team and reports to the Senior Director of GTM DAA.
In this role, you will partner closely with Sales, Marketing, and RevOps leaders to drive data-informed decision making, scale experimentation, and unlock growth through advanced analytics, machine learning model, and AI data products. You will play a critical role in shaping how Snowflake leverages data and AI to accelerate pipeline, improve conversion, and optimize the customer lifecycle.
Work Location: This position is based exclusively in Menlo Park, CA. Alternative locations are not available at this time.
What You'll Do
  • Own GTM Data Science strategyDefine and execute the roadmap for data science across pipeline generation, sales productivity, and customer growth.
  • Drive measurable business impactDeliver insights, models, and recommendations across areas such as marketing attribution, forecasting, segmentation, lead scoring, and next best action.
  • Partner with GTM leadershipAct as a trusted advisor to senior stakeholders across Sales, Marketing, and RevOps, influencing strategic planning and operational decisions.
  • Build and scale a high-performing teamRecruit, develop, and lead a team of data scientists, fostering a culture of strong execution, technical excellence, and business impact.
  • Establish experimentation and measurement frameworksLead the design and scaling of experimentation, causal inference, and performance measurement across the GTM funnel.
  • Strengthen data foundationsPartner with Analytics Engineering and Business Analytics teams to ensure trusted data models, consistent metrics, and scalable pipelines.
  • Advance AI in GTMIdentify and deploy AI-driven solutions including lead prioritization, customer segmentation, churn prediction, and sales recommendations.

What We're Looking For
  • 10+ years of experience in data science, analytics, or a related field, with 5+ years in leadership roles
  • Proven experience supporting GTM functions in a B2B SaaS or high-growth technology company
  • Strong track record of delivering measurable impact through advanced analytics and/or machine learning
  • Experience partnering with senior stakeholders across Sales, Marketing, and RevOps
  • Strong technical foundation in SQL and Python, with experience working on modern data platforms such as Snowflake
  • Experience building and scaling teams in fast-paced, high-growth environments
  • Deep understanding of experimentation, forecasting, and customer lifecycle analytics

Nice to Have
  • Experience leading ML projects in GTM domains, such as lead scoring, propensity modeling, churn prediction, and next best action
  • Hands-on experience building or deploying models for lead prioritization and propensity scoring to drive pipeline efficiency and conversion
  • Experience with data enrichment strategies, including integrating third-party data sources to enhance customer profiles, segmentation, and targeting
  • Familiarity with modern data stack tools
  • Experience applying AI/ML to GTM use cases in enterprise environments

Every Snowflake employee is expected to follow the company's confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company's data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we're scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

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