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Data Science Analytics Jobs in California (NOW HIRING)

Anthropic

Analytics Data Engineer

San Francisco, CA

$134.90K - $162K/yr

About the Role As an Analytics Engineer, you will be an early member of the Data Science & Analytics team building the foundation to scale analytics across our organization. You will collaborate with ...

Discord

Senior Data Scientist, Analytics

San Francisco, CA · On-site

$196K - $220.50K/yr

As a member of the Data Science & Analytics team, you will help Discord achieve its mission of making it easier and more fun for people to talk and hang out before, during, and after playing games.

Apple

Sr. Data Science Leader - iCloud

Cupertino, CA · On-site

$83 - $111/hr

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 directly influence ...

Apple

App Store Data Scientist

Cupertino, CA · On-site

... Data Science & Analytics for Apple Services to support transaction and subscription businesses across App Store, Apple Music, Apple TV+, Apple Arcade, Apple One, and other services! You will play a ...

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How much do data science analytics jobs pay per hour?

As of May 29, 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 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 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 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
Senior Data Scientist - Growth Measurement

Senior Data Scientist - Growth Measurement

Roblox

San Mateo, CA

Other

Posted 12 days ago

Job description

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 to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY GROWTH MEASUREMENT?

In this role, you will leverage your expertise in data science, statistics, and causal inference to develop measurement framework and product to deepen our quantitative understanding of growth efforts, which includes but not limited to performance marketing efficacy, attribution modeling and incrementality measurement. You will collaborate with cross-functional teams to develop and implement data-driven products and strategies that maximize the impact of our growth initiatives. You will also report to Senior Data Science leadership on the team.

You Will:
  • Conduct comprehensive analyses and develop measurement framework for growth efforts using advanced statistical methods and causal inference methodologies
  • Collaborate with marketing, product, and engineering teams to find opportunities for improvement and build data-driven solutions.
  • Contribute to the development of a robust data infrastructure to support user growth.
  • Communicate insights and discuss recommendations with cross function partners translating complex technical concepts into actionable insights.
  • Partner with different product teams to optimize user growth strategies through insights, strategy, and leadership.
You Have:
  • A MSc, PhD, or equivalent experience in Statistics, Economics, Operations Research, Computer Science, Applied Math, Physics, Engineering, or other quantitative fields.
  • 4+ years of experience in a data science role, with a focus on marketing science and campaign evaluation.
  • Strong knowledge and practical application of statistical methods, causal inference techniques, and experimental design.
  • Experience working with large datasets and proficiency in SQL, R/Python, and data visualization tools.
  • Experience in the gaming industry and/or multisided marketplaces.

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