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Data Jobs in Berkeley, CA (NOW HIRING)

Data Scientist - San Francisco We are seeking a talented and experienced Data Scientist to join our dynamic team in San Francisco. As a Data Scientist, you will play a pivotal role in harnessing data ...

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Execute Data labelling and annotation tasks across speech and voice datasets. * Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A FIT IF YOU'RE... * A ...

Execute Data labelling and annotation tasks across speech and voice datasets. * Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A FIT IF YOU'RE... * A ...

Data Scientist (Growth)

San Francisco, CA · On-site

$100 - $140/hr

Role As a Data Scientist at Rox, you will power the intelligence layer behind the world's first revenue operating system. You'll be responsible for the metrics, insights, and analytical frameworks ...

About the Role The Fraud Data Science team safeguards Robinhood and its customers by detecting and preventing fraud and abuse across our platform. We leverage machine learning and analytics to combat ...

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Data information

See Berkeley, CA salary details

$56.3K

$202.1K

$298.2K

How much do data jobs pay per year?

As of Aug 7, 2026, the average yearly pay for data in Berkeley, CA is $202,055.00, according to ZipRecruiter salary data. Most workers in this role earn between $163,500.00 and $208,200.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a data analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

Is it hard to get a data job?

Getting a data job can be competitive, as it often requires strong skills in data analysis, programming, and tools like SQL or Python. Relevant experience, certifications, and a solid portfolio can improve chances of securing a position in this field.

What are different jobs that work with data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

What are careers in data?

Careers in data include roles such as data analyst, data scientist, data engineer, and database administrator. These jobs involve collecting, analyzing, and interpreting data to support decision-making, often requiring skills in programming, statistics, and data visualization tools like SQL, Python, or R.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

What are the most commonly searched types of Data jobs in Berkeley, CA? The most popular types of Data jobs in Berkeley, CA are:
What are popular job titles related to Data jobs in Berkeley, CA? For Data jobs in Berkeley, CA, the most frequently searched job titles are:
What cities near Berkeley, CA are hiring for Data jobs? Cities near Berkeley, CA with the most Data job openings:
Infographic showing various Data job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $202,055 per year, or $97.1 per hour.

Data Scientist

Find Data Science

San Francisco, CA

Full-time

Posted yesterday

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Job description

Data Scientist - San Francisco

We are seeking a talented and experienced Data Scientist to join our dynamic team in San Francisco. As a Data Scientist, you will play a pivotal role in harnessing data to drive strategic decision-making processes and enhance our product offerings. You will work within a collaborative, innovative environment where your insights will shape our business strategies and help us remain competitive in an increasingly data-driven world.

Your expertise in data analysis, machine learning, and statistical modeling will enable you to tackle complex business challenges. By transforming raw data into actionable insights, you will directly contribute to our mission of providing exceptional products and services that meet the needs of our clients and customers.

Key Responsibilities
  • Analyze large datasets to uncover trends, patterns, and insights that will inform business strategies.
  • Develop, implement, and maintain advanced machine learning models to optimize company performance.
  • Collaborate with cross-functional teams to integrate data-driven solutions into existing business processes.
  • Create visualizations and dashboards to present findings to various stakeholders effectively.
  • Conduct experiments and statistical analysis to evaluate the effectiveness of business strategies.
  • Stay updated on industry trends and best practices regarding data science methodologies and technologies.
  • Mentor junior data analysts and contribute to the development of their technical skills.
  • Document methodologies and processes to ensure that data science projects are scalable and sustainable.
  • Assist in the data governance process to ensure data accuracy and integrity.
Requirements
  • Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field.
  • Proven experience as a Data Scientist or similar role, preferably in a fast-paced environment.
  • Strong proficiency in programming languages such as Python or R.
  • Experience with data visualization tools (e.g., Tableau, Power BI) and SQL.
  • Solid understanding of machine learning algorithms and statistical analysis techniques.
  • Excellent analytical and problem-solving skills with a keen attention to detail.
  • Strong communication skills, with the ability to convey complex data insights to non-technical audiences.
  • Ability to work collaboratively in a team-oriented environment.
  • Experience with big data technologies (e.g., Hadoop, Spark) is a plus.