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Data Science Contract Jobs in California (NOW HIRING)

Contract Compensation: $100-$150/hour Location: Remote Role Responsibilities * Design precise, task-specific grading criteria for data science deliverables. This includes exploratory data analyses ...

Job Duration: Long Term Contract (Possibility Of Extension) Company Benefits: Medical, Dental ... MS/PhD in Data Science, Computer Vision, Bioinformatics, Computational Biology, or related field ...

New

... contract award. Must be a U.S. Citizen. Must have an active Top Secret w/SCI eligibility ... Minimum of 10 years of professional experience in data science Preferred Qualifications

Data Scientist III

San Diego, CA · On-site

$125K - $207K/yr

... contract award. Must be a U.S. Citizen. Must have an active Top Secret w/SCI eligibility ... Minimum of 10 years of professional experience in data science Preferred Qualifications

Mid Data Scientist

San Diego, CA · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... as well as contract-specific affordability and organizational requirements. The projected ...

On our team, you'll use your analytical skills and data science knowledge to create real-world ... as well as contract-specific affordability and organizational requirements. The projected ...

Contract Compensation: $100-$150/hour Location: Remote Role Responsibilities * Design precise, task-specific grading criteria for data science deliverables, including exploratory data analyses ...

Showing results 21-40

Data Science Contract information

See California salary details

$23K

$108.6K

$200.7K

How much do data science contract jobs pay per year?

As of Aug 21, 2026, the average yearly pay for data science contract in California is $108,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,326.00 and $152,270.00 per year, depending on experience, location, and employer.

What is a data science contract?

A Data Science Contract job is a temporary or project-based role where a data scientist is hired for a specific period to work on data-related tasks such as analysis, machine learning, or model development. These roles can be short-term (a few months) or long-term but lack the benefits and job security of full-time employment. Contract data scientists often work with multiple clients, bringing expertise to solve business problems without a long-term commitment.

What kinds of projects and day-to-day tasks can I expect as a data science contract professional?

As a Data Science Contract professional, you can expect to work on a variety of projects such as developing predictive models, analyzing large datasets, creating data visualizations, or advising organizations on best practices for data-driven decision making. Your day-to-day tasks may involve collaborating closely with clients or internal stakeholders to clarify objectives, cleaning and preparing data, developing algorithms, and presenting your findings in clear, actionable formats. Projects often vary in length and scope, offering exciting opportunities to tackle new business challenges across different industries. Flexibility and effective time management are essential, as balancing project deadlines and adapting quickly to new tools or domains are common aspects of contract-based work.

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

To thrive as a Data Science Contract professional, you need a strong foundation in statistical analysis, machine learning, data manipulation, and advanced proficiency in programming languages such as Python or R, typically supported by a relevant degree. Experience with data visualization tools, cloud platforms, and certifications like AWS Certified Data Analytics or Microsoft Certified: Data Scientist are highly valued. Excellent communication, problem-solving abilities, and adaptability are crucial soft skills for collaborating with diverse teams and interpreting client needs. These skills ensure that contract-based data scientists can deliver actionable insights, adapt to new environments, and effectively address client-specific problems within limited project timelines.

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

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

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

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

What cities in California are hiring for Data Science Contract jobs?

Cities in California with the most Data Science Contract job openings:

Infographic showing various Data Science Contract job openings in California as of August 2026, with employment types broken down into 54% Full Time, and 46% Contract. Highlights an 100% In-person job distribution, with an average salary of $108,565 per year, or $52.2 per hour.

Sr. Data Science, Ops Decision Systems

Socket.dev

Palo Alto, CA • On-site

$150 - $184/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


Job description

About Rivian

Rivianis on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.


As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.


Role Summary

This is a technical individual contributor role that designs, builds, and operates the operations-side modeling and simulation systems for Rivian’s remarketing business: inventory allocation, reconditioning capacity, disposition timing, logistics, and operating expense. The role develops multi-variable simulation and optimization models in Python and Databricks within Git-versioned repositories with code review, automated testing, and CI/CD, and translates operational levers into dollar-denominated outcomes.


The Sr. Data Science, Ops Decision Systems role combines applied data science, analytics engineering, and operations ownership: the role both engineers the simulation systems and is accountable for the quality of the operational decisions they inform. Success is measured by the technical robustness of the systems built and the integrity of the plans they produce.


Responsibilities

  • Design, build, and operate production simulation and optimization systems. Develop Python-based simulation models in Databricks as a member of a highly technical team designing interconnected models. Work in Git-versioned repositories with merge-request review, automated testing, and CI/CD pipelines (GitLab), and apply AI-assisted and agentic development workflows as a standard part of the engineering stack.

  • Statistical and optimization model development. Design, validate, and maintain the models that drive operational decisions: reconditioning capacity and throughput models, operating-expense models, inventory allocation optimization, and disposition-timing models. Apply statistical, machine learning, and optimization methods, with backtesting and production performance monitoring.

  • Operations data products and pipelines. Build and maintain the data models and pipelines that describe operational performance, covering inventory state, auction outcomes, reconditioning throughput and cost, logistics, and allocation, with data contracts, tests, and documentation that allow downstream decision systems and planning tools to consume them reliably.

  • AI-augmented engineering. Apply AI-assisted and agentic development workflows as a first-class part of the engineering stack. Evaluate and integrate AI tooling into production engineering workflows and set the patterns the team follows.

  • Network and capacity scenario engineering. Build and run multi-variable scenario models that optimize the physical infrastructure footprint, vehicle movement strategies, reconditioning capacity plans, and operational workflows across Remarketing operations. Vary levers systematically and narrow many candidate plans to defensible recommendations.

  • Financial efficiency optimization. Model and trend resource-efficiency outcomes across all areas of operating expense, including reconditioning, storage capacity and utilization, and vehicle movements, and translate operational decisions into projected P&L outcomes over multi-year horizons.

  • Supply deployment with business partners. Model the prioritization of units for reconditioning, the routing of vehicles toward demand, and the strategic deployment of inventory to maximize profit and stability. Work with customer-focused colleagues to integrate demand signals, and operationalize recommendations with Remarketing operations leadership, internal service and delivery partners, and external third-party partners.


Qualifications

  • Proficiency with Python, SQL, and Databricks (or equivalent warehouse/lakehouse platform); experience with dbt or equivalent transformation frameworks.

  • Experience with Git-based engineering workflows, code review, and CI/CD pipelines (GitLab or equivalent).

  • Demonstrated experience owning production data infrastructure end-to-end, including data modeling, pipeline orchestration, testing, and deployment.

  • Demonstrated ability to design and validate applied simulation and optimization models, including capacity modeling, operational optimization, or multi-variable simulation over multi-year horizons.

  • Experience reasoning about supply/demand constraints, depreciation mechanics, holding costs, and operating expense, and translating operational decisions into dollar-denominated outcomes.

  • Demonstrated ability to translate ambiguous operational questions into production data products and durable models.


Preferred Qualifications

  • Bachelor’s degree or higher in a quantitative or technical field (Computer Science, Data Science, Statistics, Mathematics, Industrial Engineering, or similar).

  • Experience applying machine learning or deep learning methods to capacity, logistics, or operational forecasting problems.

  • Experience integrating external APIs and third-party data sources into production data systems.

  • Experience with AI-assisted development workflows and agentic coding tools.

  • Experience in automotive, marketplace, e-commerce, supply chain, or adjacent operations domains.

  • Familiarity with BI and analytics tools such as Hex, Looker, or equivalent.


Pay Disclosure

The salary range for this role is $146,900 to $183,600 for Palo Alto, CA based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.


The successful candidate may be eligible for annual performance bonus and equity awards.


We offer a comprehensive package of benefits for full-time and part-time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short-term disability insurance, and long-term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian’s 401(k) Plan and Employee Stock Purchase Plan if you meet certain eligibility requirements. Full-time employee coverage is effective on their first day of employment. Part-time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com.


Equal Opportunity

Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.


Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com.


Candidate Data Privacy and Technology

Rivian may collect, use and disclose your personal information or personal data (within the meaning of the applicable data protection laws) when you apply for employment and/or participate in our recruitment processes (“Candidate Personal Data”). This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of (i) tracking interactions with our recruiting system; (ii) carrying out, analyzing and improving our application and recruitment process, including assessing you and your application and conducting employment, background and reference checks; (iii) establishing an employment relationship or entering into an employment contract with you; (iv) complying with our legal, regulatory and corporate governance obligations; (v) recordkeeping; (vi) ensuring network and information security and preventing fraud; and (vii) as otherwise required or permitted by applicable law.


Rivian may share your Candidate Personal Data with (i) internal personnel who have a need to know such information in order to perform their duties, including individuals on our People Team, Finance, Legal, and the team(s) with the position(s) for which you are applying; (ii) Rivian affiliates; and (iii) Rivian’s service providers, including providers of background checks, staffing services, and cloud services.


Rivian may transfer or store internationally your Candidate Personal Data, including to or in the United States, Canada, the United Kingdom, and the European Union and in the cloud, and this data may be subject to the laws and accessible to the courts, law enforcement and national security authorities of such jurisdictions.


How We Use AI in Our Hiring Process: To ensure transparency, we want candidates to know that Rivian uses iCIMS Talent Cloud Artificial Intelligence (TCAI) and AI-enabled tools to assist with screening, reviewing, organizing and highlighting profiles and applications that match the key requirements for each role. AI does not make hiring decisions: Qualified candidate applications are reviewed by a member of our team, and all decisions throughout the process are made by humans. We use AI to support efficiency and consistency, not to replace human judgment. We are committed to a fair, thoughtful, and equitable experience for every candidate.


Participation in AI profile matching is entirely voluntary. If you prefer that your profile not be used in this process, you can opt out at any time. Opting out means your profile will be excluded from automated matching and will not be surfaced for additional roles through this system. Your current application remains active and will not be affected in any way.


Please note that we are currently not accepting applications from third party application services.

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