Hourly Python Data Science Jobs in Santa Clara, CA

Rivian is 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. 

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.

• 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.

• 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.

• 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.

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.

You can apply for this role through careers.rivian.com (or through internal-careers-rivian.icims.com if you are a current employee). This job is not expected to be closed any sooner than August 31, 2026.

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.

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.

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.

• 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.

• 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.