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Temporary Data Scientist Machine Learning Jobs in California

Apple

Machine Learning - Data Scientist

Sunnyvale, CA

$150K - $277K/yr

... Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep ... scientists, and ML Infrastructure engineers to deliver amazing user experiences! Description ...

Nash, Inc.

Senior Data Scientist

San Francisco, CA · On-site +1

What you'll bring * 4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a ... related quantitative role. * Experience in logistics, marketplaces, supply chain, operations ...

CYNET SYSTEMS

Principal Data Scientist

Oakland, CA · On-site

$128 - $148/hr

Master's Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field. * Experience in Data Science ...

Nash

Senior Data Scientist

San Francisco, CA · On-site

$180 - $240/hr

What you'll bring * 4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a ... related quantitative role. * Experience in logistics, marketplaces, supply chain, operations ...

VSolvit, LLC.

DATA SCIENTIST II

Norco, CA · On-site

$115 - $130/hr

DATA SCIENTIST II Full Time VS CA NORCO, Norco, CA, US 7 days ago Requisition ID: 1577 Salary Range ... In this role, you will apply advanced data analytics and machine learning techniques to explore ...

Apple

Data Scientist

Sunnyvale, CA · On-site

Working at the intersection of machine learning, data science, and product quality, you will influence critical decisions through data-driven insights and technical leadership. You will collaborate ...

Walmart

Senior, Data Scientist

South San Francisco, CA · On-site

$117K - $234K/yr

We are seeking a Senior Data Scientist with a strong foundation in machine learning, information ... Experience building machine learning, Deep Learning models, GenAI applications and deploying to ...

Walmart

Senior, Data Scientist

Daly City, CA · On-site

$117K - $234K/yr

We are seeking a Senior Data Scientist with a strong foundation in machine learning, information ... Experience building machine learning, Deep Learning models, GenAI applications and deploying to ...

Walmart

Senior, Data Scientist

Cupertino, CA · On-site

$117K - $234K/yr

We are seeking a Senior Data Scientist with a strong foundation in machine learning, information ... Experience building machine learning, Deep Learning models, GenAI applications and deploying to ...

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All JobsData Scientist Machine Learning JobsTemporary Data Scientist Machine Learning JobsTemporary Data Scientist Machine Learning Jobs in California

Temporary Data Scientist Machine Learning information

What is the difference between Temporary Data Scientist Machine Learning vs Temporary Data Analyst?

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

What does a temporary data scientist specializing in machine learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a temporary data scientist specializing in machine learning?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary data scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.
What are the most commonly searched types of Data Scientist Machine Learning jobs in California? The most popular types of Data Scientist Machine Learning jobs in California are:
What are popular job titles related to Temporary Data Scientist Machine Learning jobs in California? For Temporary Data Scientist Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Temporary Data Scientist Machine Learning jobs in California look for? The top searched job categories for Temporary Data Scientist Machine Learning jobs in California are:
What cities in California are hiring for Temporary Data Scientist Machine Learning jobs? Cities in California with the most Temporary Data Scientist Machine Learning job openings:
Temporary Data Scientist Machine Learning jobs near you
Infographic showing various Temporary Data Scientist Machine Learning job openings in California as of August 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 100% In-person job distribution.

Machine Learning / Data Scientist

PROPRIUS

Bodega Bay, CA

$110K - $140K/yr

Full-time

Re-posted 21 days ago

Job description

Machine Learning Engineer

Location: San Francisco, CA

Sponsorship: No

Relocation: No

Industry: Machine Learning

Our client is a digital invention agency focused on machine learning methodologies, enterprise mobile and web applications, eCommerce, augmented reality and IoT. They look to innovatively make this world a better place with each and every product, system, idea and app they release.

Job Summary

Our client is looking for a machine learning engineer to join our existing ML team in developing and refining a predictive application.

The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.

You must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. You must have a proven ability to drive business results with their data-based insights. You must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

As a ML Engineer, you will:

  • Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business solutions
  • Mine and analyze data from databases to drive optimization and improvement of product development, marketing techniques and business strategies
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques
  • Develop custom data models and algorithms to apply to data sets
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes
  • Coordinate with different functional teams to implement models and monitor outcomes
  • Develop processes and tools to monitor and analyze model performance and data accuracy

For this role you will need:

  • Strong with Statistics and can code in either R, Python, Java and Scala
  • Experience with designing and building using micro-services architectural pattern, web APIs using dotnet core & C#
  • Experience and passion for simulations, optimization, neural networks, artificial intelligence (deep learning and machine learning)
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, GIT, SQL, etc.
  • Able to understand statistical solutions and execute similar activities
  • Experience in data wrangling and advanced analytic modeling
  • Strong communication and organizational skills and has the ability to deal with ambiguity while juggling multiple priorities and projects at the same time
  • Experience visualizing/presenting data for stakeholders using: Seaborn, Business Objects, D3, ggplot, etc.
  • Ability to investigate the feasibility and data requirements necessary to develop an ML solution for a given problem
  • Ability to design, build and test production ready ML-based products while interpreting and explaining the basis for predictions generated by ML models

The perfect candidate will have:

  • Knowledge and experience using one or more of the following, or similar, machine learning software frameworks: CAFFE, Torch 7, Keras and Tensorflow
  • Experience building production-ready NLP or information retrieval systems
  • Hands-on experience with NLP tools, libraries and corpora (e.g. NLTK, Stanford CoreNLP, Wikipedia corpus, etc.)

PROPRIUS is an AI Industry recruiting firm. We’re lucky enough to recruit the best candidates into the most exciting companies all over the United States. We deliver performance.
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