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Data Science Analytics Jobs in California (NOW HIRING)

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

Strong skills in scientific data analyses, modeling, visualization and communication of results. * Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

Strong skills in scientific data analyses, modeling, visualization and communication of results. * Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB ...

Align Technology

Sr. Data Scientist

San Jose, CA · On-site

... data science skills, including data extraction, exploratory and confirmatory analysis, modeling, and validation • Design and develop advanced ML or Agentic AI solutions, including systems that ...

Fanatics Collectibles

Data Scientist

Los Angeles, CA · On-site

Clearly communicate analytical findings and recommendations to technical and non-technical stakeholders. What You'll Need * Bachelor's degree in Statistics, Mathematics, Computer Science, Data ...

Align Technology

Sr. Data Scientist

San Jose, CA · On-site

... data science skills, including data extraction, exploratory and confirmatory analysis, modeling, and validation • Design and develop advanced ML or Agentic AI solutions, including systems that ...

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 ...

Apple

Sr. Data Science Leader - iCloud

Cupertino, CA · On-site

$267K - $401K/yr

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 ...

Knit Health

Senior Data Scientist

San Francisco, CA

$140K - $175K/yr

As a senior member of our growing data science team, you will lead the design, curation, and analysis of complex, multi-system healthcare datasets-including EHR and claims data-powering our clinical ...

Roblox

[2026] Data Scientist, Social

San Mateo, CA · On-site

$185K - $221K/yr

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 ...

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All JobsData Science Analytics JobsData Science Analytics Jobs in California

Data Science Analytics information

See California salary details

$24

$54

$93

How much do data science analytics jobs pay per hour?

As of Aug 7, 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?

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 August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $112,382 per year, or $54 per hour.

Data Science

Adidev Technologies Inc

San Francisco, CA • Remote

Full-time

Re-posted 17 days ago

Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred

  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME

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