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Data Science Jobs in Berkeley, CA (NOW HIRING)

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

As a Delivery team, this Department uses industry leading data science and change management practices to drive transition to the sustainable grid of the future. The Department works cross ...

CYNET SYSTEMS

Data Scientist

San Ramon, CA · On-site

$93 - $98/hr

Provides hands-on execution and implementation of data science models. * Translates business analysis needs into well-defined data science problems, selecting appropriate models and algorithms.

Swayable

Research Data Scientist

San Francisco, CA · On-site

Swayable is a fast-growing AI and automated data science platform that measures public opinion and the impact of messages and advertising content on it. As a Research Data Scientist, you will conduct ...

Adobe

Sr. Manager, People Data Science

San Francisco, CA · On-site

$161K - $303K/yr

The Opportunity The Sr. Manager of People Data Science will lead and develop the data science function within the Employee Experience team. This role will report to the Head of People Analytics and ...

Visa

Sr. Manager, Data Science

Foster City, CA

Lead, execute, and deliver data science and strategic analytics projects that support Visa's internal Consumer Payments business priorities and align with Visa's long-term growth agenda. * Partner ...

Visa

Sr. Manager, Data Science

Foster City, CA · On-site

Lead, execute, and deliver data science and strategic analytics projects that support Visa's internal Consumer Payments business priorities and align with Visa's long-term growth agenda. * Partner ...

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Showing results 41-60

All JobsData Science JobsData Science Jobs in Berkeley, CA

Data Science information

See Berkeley, CA salary details

$45.9K

$150.3K

$240.6K

How much do data science jobs pay per year?

As of Aug 9, 2026, the average yearly pay for data science in Berkeley, CA is $150,286.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,600.00 and $166,500.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Berkeley, CA? The most popular types of Data Science jobs in Berkeley, CA are:
What are popular job titles related to Data Science jobs in Berkeley, CA? For Data Science jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Berkeley, CA look for? The top searched job categories for Data Science jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Data Science jobs? Cities near Berkeley, CA with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Berkeley, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, 4% Hybrid, and 16% Remote job distribution, with an average salary of $150,286 per year, or $72.3 per hour.

Data Scientist

Avani Technology Solutions, Inc.

San Francisco, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Role: Data Scientist
Location: San Francisco, CA
Duration: 6+ Months
Team Overview:
The Digital Catalyst Team is a new enterprise team that is responsible for working collaboratively with the lines of business to implement consumer grade mobile and analytical solutions across various user groups (e.g., field users, office workers, etc.). This includes, but is not limited to:
  • Deploying best-in-class / rapid delivery capability for mobile solutions.
  • Simplifying, improving, and standardizing business work management processes for mobile needs.
  • Delivering high value analytics across all Lines of Businesses.
  • Rapid delivery of web applications.

Digital Catalyst consists of a staff of highly skilled professionals working together to produce mobile solutions following an agile methodology and design thinking. We are a "start-up" department within IT and building driven and creative mobile development team. We take the time to understand our partners' needs and translate those into solutions that delight our users. Our goal is to deliver products with intuitive user experience that will improve employees' and customer's safety, productivity and overall well-being.
Position Summary:
We are seeking an experienced Data Scientist in the Digital Catalyst Team who will provide strong execution and delivery of data science. Working as a part of the product team, this Data Scientist will translate business needs into advanced analytics and machine learning models. The successful candidate will be responsible for model selection and identification of appropriate training data sets; building, training, and evaluating models; and delivering results to the business on a regular cadence. This role is part of a fully Agile Scrum team, so the data scientist will work alongside a product owner, technical lead, and team of developers and data engineers to support delivery of high-value analytics and software products.
Position Responsibilities:
  • Leads development of high complexity models and training sets
  • Provides hands-on execution and implementation of data science models
  • Translates business analysis needs into well-defined data science problems, and selecting appropriate models and algorithms and communicates model evaluation and implications of results back to stakeholders
  • Recognizes and prioritizes the most important work related to data science models to achieve highest operational impact for analytics in the business
  • Balances tradeoffs among analytics value, model development methods and design and technologies used to implement data science models with a bias toward action
  • Performs collaborative work on data science problems and mentor junior data scientists
  • Creates shared process models, business objects, activity diagrams and process documentation to effectively articulate multiple views of the business solutions that support technical architecture.
  • Manages development of quantitative models and tools.
  • Collaborates with leaders, other LOBs, and business partners to work on issues, projects or activities.
  • Develops new or revises complex models to predict business demand trends, and volume and expenditures forecasts capacity analysis, and various other metrics to identify potential opportunities.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
  • Partners with leaders to drive high performance in their lines of business.
  • Develop deep understanding of business drivers and financial levers to provide strategic decision support.
  • Oversees resolution of complex projects and programs.
  • Develops and maintains up-to-date detailed project schedules and work plans.
  • Performs analysis on complex data models requiring customized reports and data and presents recommendations.

Minimum Education/Skills:
  • Bachelor's Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience
  • Job-related experience, 8 years, OR Master's Degree and job-related experience, 6 years, OR Doctorate Degree and job-related experience, 3 years
  • Experience in data modeling, 5yrs

Desired Education / Skills:
  • PhD in engineering or a related field (computer science, natural sciences, mathematics)
  • Experience with Python, R, Scala, SQL
  • Experience developing solutions with Pandas/Scikit-learn, Spark or comparable technologies
  • Experience data science notebooks (Jupyter, Zeppelin or other)
  • Experience with AWS, Azure, cloud computing technologies
  • Scrum team experience
  • Energy industry experience
  • Experience designing efficient data science workflows and database architecture for data science purposes
  • Experience with forecasting, Bayesian networks, and graph analytics
  • Strong statistics experience
  • Experience with software development methodologies and software engineering principles
  • Knowledge of program management theories, concepts, methods, best practices, and techniques as needed to perform at the job level
  • Knowledge of relevant programming languages - for example Visual Basic, Ladder Logic,
  • Programmable Logic Controller, C, SharePoint, HTML, Java, Adobe - as needed to perform at the job level
  • Competency in knowing the most effective and efficient processes to get things done, with a focus on continuous improvement
  • Knowledge of principles, techniques, and procedures used for production and design of technology based equipment and systems as needed to perform at the job level
  • Knowledge of statistical theories, concepts, methods, best practices, and analyses as needed to perform at the job level
  • Ability to develop reports, models, and simulations as needed to perform at the job level
  • Competency in developing and delivering multi-mode communications that convey a clear
  • understanding of the unique needs of different audiences
  • Knowledge of data model design philosophies and methodologies for data warehouse and OLTP systems

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