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Business Science Jobs in California (NOW HIRING)

BNBuilders

Business Development Manager

San Mateo, CA · On-site

$150K - $250K/yr

Bachelors degree in business, science or other related discipline or Associates degree and related experience. * Effective communicator, able to deliver clear, concise and consistent messages, both ...

BNBuilders

Business Development Manager

San Mateo, CA

$150K - $250K/yr

Bachelors degree in business, science or other related discipline or Associates degree and related experience. * Effective communicator, able to deliver clear, concise and consistent messages, both ...

BNBuilders

Business Development Manager

San Diego, CA · On-site

$150K - $250K/yr

Bachelors degree in business, science or other related discipline or Associates degree and related experience. * Effective communicator, able to deliver clear, concise and consistent messages, both ...

BNBuilders

Business Development Manager

San Diego, CA

$150K - $250K/yr

Bachelors degree in business, science or other related discipline or Associates degree and related experience. * Effective communicator, able to deliver clear, concise and consistent messages, both ...

Amazon

Applied Scientist III - AMZ10362489

Santa Clara, CA · On-site

$192K - $260K/yr

... business, science, or engineering.#0000 PREFERRED QUALIFICATIONS Please see and the position requirements above. Amazon is an equal opportunity employer and does not discriminate on the basis of ...

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All JobsBusiness Science JobsBusiness Science Jobs in California

Business Science information

See California salary details

$27.6K

$84.1K

$176.7K

How much do business science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for business science in California is $84,063.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,800.00 and $110,000.00 per year, depending on experience, location, and employer.

What is a business science?

A Business Science job involves using data science, analytics, and business strategy to drive decision-making and improve business performance. Professionals in this field analyze large datasets, develop predictive models, and use statistical methods to provide insights that support organizational goals. They often work in roles such as business analysts, data scientists, or strategy consultants, applying analytical techniques to solve real-world business challenges. The role requires a mix of technical skills, such as programming and machine learning, along with business acumen and problem-solving abilities.

What are the typical projects or responsibilities for a business science professional?

A Business Science professional typically works on projects involving business process optimization, forecasting, market analysis, and identifying data-driven strategies to improve company performance. Responsibilities often include gathering and analyzing large datasets, developing predictive models, and collaborating closely with cross-functional teams such as marketing, finance, and operations. You may also be tasked with presenting actionable insights to stakeholders and contributing to strategic business initiatives. The role provides a dynamic environment that blends technical analysis with real-world business impact, making every day both challenging and rewarding.

What are the key skills and qualifications needed to thrive in the business science position, and why are they important?

To thrive in a Business Science role, you need strong analytical, data management, and problem-solving skills, often supported by a degree in business analytics, data science, or a related field. Familiarity with analytical tools such as SQL, Python, R, and business intelligence platforms like Tableau or Power BI, along with relevant certifications, is highly beneficial. Excellent communication, teamwork, and the ability to translate complex data into actionable business strategies are key soft skills. These abilities enable professionals to effectively leverage data insights to drive decision-making and deliver measurable business value.

What can you do with a business science degree?

A business science degree prepares individuals for roles in data analysis, management, consulting, and strategic planning. Graduates often work in industries such as finance, marketing, or operations, utilizing skills in analytics, problem-solving, and business tools like Excel or SQL.

What do business scientists do?

Business scientists analyze data to identify trends, develop insights, and support decision-making within organizations. They often use statistical tools, machine learning, and data visualization to solve complex business problems and improve strategies.

What are the most commonly searched types of Business Science jobs in California?

The most popular types of Business Science jobs in California are:

What are popular job titles related to Business Science jobs in California?

For Business Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Business Science jobs in California look for?

The top searched job categories for Business Science jobs in California are:

What cities in California are hiring for Business Science jobs?

Cities in California with the most Business Science job openings:

Business Science jobs near you
Infographic showing various Business Science job openings in California as of August 2026, with employment types broken down into 50% Part Time, and 50% Contract. Highlights an 100% In-person job distribution, with an average salary of $84,063 per year, or $40.4 per hour.

Research Data Scientist, Brand Advertising, YouTube Ads

Socket.dev

Mountain View, CA • On-site

$147 - $210/hr

Other

Posted 3 days ago

New

Job description

MINIMUM QUALIFICATIONS:

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • 3 years of work experience with online marketplace design, adtech, and causal inference.

PREFERRED QUALIFICATIONS:

  • PhD degree in a quantitative field such as Engineering, Computer Science, Mathematics, Statistics, Economics, or Business Science.
  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
ABOUT THE JOB

As a Data Scientist in the Brand Ads Quality team, you will leverage eclectic quantitative repertoire, spanning operations research, game theory, statistics, and machine learning skills, to build industry-leading optimization solutions that will enable advertisers to divert a greater share of marketing budgets to YouTube where user engagement outpaces all other media channels. You will be included in tasks such as aiming relevance, creative recommendation, bidding optimization, and impact measurement. You will grow in an environment, proactively identify opportunities to enhance a business ecosystem, and showcase project ownership from solution design to engineering implementation and data-driven analyses culminating in production launch. You will partner with Software Engineers (SWEs) and Project Managers (PMs).

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google https://www.google.com/about/careers/applications/benefits/.

RESPONSIBILITIES
  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer and provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate using specialized knowledge and design and evaluate models to mathematically express and solve defined problems with limited precedent.
  • Gather information, business goals, priorities, and organizational context around questions to answer and existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python); separately format, re-structure, or validate data to ensure quality; and review the dataset to ensure it is ready for analysis.
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