Data Science Engineer Visa Sponsorship Jobs in California
California is the top state for data science engineer visa sponsorship, driven by major tech employers across the San Francisco Bay Area, Los Angeles, and San Diego. Companies like Google, Meta, Apple, and Salesforce regularly sponsor H-1B visas for these roles, with particularly high concentration in Silicon Valley and the broader South Bay.
See All Data Science Engineer JobsOverview
Showing 5 of 4,986+ Data Science Engineer Jobs in California with Visa Sponsorship jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 4,986+ Data Science Engineer Jobs in California with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Science Engineer Jobs in California with Visa Sponsorship.
Get Access To All JobsABOUT TERRA AI
We are building the state-of-the-art AI platform for the discovery and development of clean energy and mineral resources. We bring the most advanced techniques in generative AI, foundation modeling, and autonomous decision optimization to tackle the most important problems in the geosciences. These systems can help more reliably identify critical resource deposits, more rapidly measure and characterize them, and design more efficient and sustainable production plans.
We are backed by Khosla Ventures and other leading venture investors. We are now looking to grow our team from ~15 to ~30 by the end of the year to continue to mature our technology and support deployment with our world-class mineral and clean energy partners.
ROLE
Own customer data ingestion and build QA/QC workflows that make messy, real-world geoscience data usable at scale. This role blends hands-on GIS execution with data engineering. You will run GIS workflows for projects while also building automation to reduce manual work and improve repeatability.
WHAT YOU’LL DO
Run project GIS workflows
- Prepare, curate, and serve complex client datasets across surface GIS and 3D subsurface contexts.
- Use GIS tools day to day to assemble layers, validate spatial alignment, and produce project outputs.
- Create high-quality maps and figures for internal review and client deliverables, including cartographic polish when needed.
Build ingestion and QA/QC systems
- Ingest and normalize datasets such as:
- Drillhole and drill core data (major focus)
- Airborne and other geophysical survey datasets
- Supporting geospatial layers and project metadata
- Standardize disparate client formats into a unified framework to support modeling workflows.
- Build automated QA/QC checks that catch issues early, including:
- Coordinate reference systems and transformations
- Units, conventions, missingness, duplicates, and outlier detection
- Schema validation, metadata sanity, provenance tracking
- Cross-dataset consistency checks (for example, collars vs surveys vs intervals)
- Create reproducible ingestion pipelines that reduce manual work and shorten time-to-first-model.
- Act as a primary liaison for geology and ML teams, providing spatial analysis and visual validation of outputs against client-provided datasets.
- Document standards and build tooling that is usable by other engineers and scientists.
REQUIREMENTS
- Formal training and hands-on experience in GIS, geospatial data science, geoscience data systems, or a closely related discipline.
- Strong practical ability with messy data, including building pipelines, validations, and repeatable transformations.
- Proficiency with modern GIS software. Experience with QGIS and/or ArcGIS Pro is strongly preferred.
- Experience with spatial data administration: coordinate system transformations, managing large datasets, and working with spatial databases.
- Ability to build in Python for data workflows.
NICE TO HAVE
- Experience producing publication-quality technical figures (Adobe Creative Suite or similar).
- Familiarity with subsurface or geo-modeling tools (Leapfrog, SKUA GOCAD, Mira Geoscience Analyst, or similar).
- Experience with drillhole data standards and common exploration formats.
- Experience with geophysical datasets and processing concepts.
- Experience designing QA/QC systems where wrong data has real cost.
ABOUT TERRA AI
We are building the state-of-the-art AI platform for the discovery and development of clean energy and mineral resources. We bring the most advanced techniques in generative AI, foundation modeling, and autonomous decision optimization to tackle the most important problems in the geosciences. These systems can help more reliably identify critical resource deposits, more rapidly measure and characterize them, and design more efficient and sustainable production plans.
We are backed by Khosla Ventures and other leading venture investors. We are now looking to grow our team from ~15 to ~30 by the end of the year to continue to mature our technology and support deployment with our world-class mineral and clean energy partners.
ROLE
Own customer data ingestion and build QA/QC workflows that make messy, real-world geoscience data usable at scale. This role blends hands-on GIS execution with data engineering. You will run GIS workflows for projects while also building automation to reduce manual work and improve repeatability.
WHAT YOU’LL DO
Run project GIS workflows
- Prepare, curate, and serve complex client datasets across surface GIS and 3D subsurface contexts.
- Use GIS tools day to day to assemble layers, validate spatial alignment, and produce project outputs.
- Create high-quality maps and figures for internal review and client deliverables, including cartographic polish when needed.
Build ingestion and QA/QC systems
- Ingest and normalize datasets such as:
- Drillhole and drill core data (major focus)
- Airborne and other geophysical survey datasets
- Supporting geospatial layers and project metadata
- Standardize disparate client formats into a unified framework to support modeling workflows.
- Build automated QA/QC checks that catch issues early, including:
- Coordinate reference systems and transformations
- Units, conventions, missingness, duplicates, and outlier detection
- Schema validation, metadata sanity, provenance tracking
- Cross-dataset consistency checks (for example, collars vs surveys vs intervals)
- Create reproducible ingestion pipelines that reduce manual work and shorten time-to-first-model.
- Act as a primary liaison for geology and ML teams, providing spatial analysis and visual validation of outputs against client-provided datasets.
- Document standards and build tooling that is usable by other engineers and scientists.
REQUIREMENTS
- Formal training and hands-on experience in GIS, geospatial data science, geoscience data systems, or a closely related discipline.
- Strong practical ability with messy data, including building pipelines, validations, and repeatable transformations.
- Proficiency with modern GIS software. Experience with QGIS and/or ArcGIS Pro is strongly preferred.
- Experience with spatial data administration: coordinate system transformations, managing large datasets, and working with spatial databases.
- Ability to build in Python for data workflows.
NICE TO HAVE
- Experience producing publication-quality technical figures (Adobe Creative Suite or similar).
- Familiarity with subsurface or geo-modeling tools (Leapfrog, SKUA GOCAD, Mira Geoscience Analyst, or similar).
- Experience with drillhole data standards and common exploration formats.
- Experience with geophysical datasets and processing concepts.
- Experience designing QA/QC systems where wrong data has real cost.
Data Science Engineer Job Roles in California
See all 4,986+ Data Science Engineer Jobs in California
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search Data Science Engineer Jobs in CaliforniaData Science Engineer Jobs in California: Frequently Asked Questions
Which companies in California sponsor visas for data science engineers?
Large tech companies including Google, Apple, Meta, Amazon, and Salesforce are among the most consistent H-1B sponsors for data science engineer roles in California. Beyond the household names, mid-size companies in fintech, healthtech, and enterprise SaaS, particularly those headquartered in the Bay Area or Los Angeles, also file substantial numbers of H-1B petitions for data engineering and machine learning positions each year.
What visa types are most common for data science engineer roles in California?
The H-1B is the most common visa for data science engineers in California, as the role typically requires at least a bachelor's degree in computer science, statistics, or a related field, satisfying the specialty occupation standard. OPT and STEM OPT are common entry points for recent graduates from California universities. Candidates with exceptional publication records or industry recognition may also qualify for the O-1A.
Which California cities have the most data science engineer sponsorship jobs?
The San Francisco Bay Area, including San Jose, Sunnyvale, Mountain View, and San Francisco itself, accounts for the largest share of data science engineer sponsorship roles in California. Los Angeles is a growing second hub, particularly in media technology and aerospace data roles. San Diego has a smaller but active cluster tied to biotech and defense contractors that also hire for these positions.
How to find data science engineer visa sponsorship jobs in California?
Migrate Mate is built specifically for international candidates seeking visa sponsorship and filters data science engineer roles by state, so you can browse California-specific openings from employers with active sponsorship histories. Rather than sorting through thousands of unfiltered postings, Migrate Mate surfaces roles where sponsorship is part of the hiring expectation, which is especially useful given the competitive volume of applications in California's tech market.
Are there any California-specific considerations for data science engineers pursuing visa sponsorship?
California's prevailing wage requirements under the H-1B program are among the highest in the country, reflecting the state's cost of living and competitive tech market. Employers filing Labor Condition Applications for Bay Area or Los Angeles positions must certify wages at or above the applicable prevailing wage level for that location. Many California universities, including UC Berkeley, UCLA, Stanford, and UCSD, also serve as active pipelines feeding sponsored data science engineering roles at nearby employers.
What is the prevailing wage for sponsored data science engineer jobs in California?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
See which data science engineer employers are hiring and sponsoring visas in California right now.
Search Data Science Engineer Jobs in California