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Remote Geospatial Data Scientist Jobs in California

Nash, Inc.

Senior Data Scientist

San Francisco, CA · On-site +1

Senior Data Scientist About Nash Nash is the autonomic logistics platform. We unify decisioning and ... Work with large, messy operational datasets, including delivery events, geospatial data, carrier ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

YO AI Labs

GIS/Geospatial Expert

San Jose, CA · Remote

$80 - $100/hr

... Science . No prior AI training experience is required. What matters most is your ability to apply ... Provide expert analysis, feedback, and practical examples related to GIS, geospatial data, remote ...

Posted today

BKF

Geospatial Technical Specialist

Riverside, CA · On-site +1

$83K - $166K/yr

This position is remote (with the ability to be in a BKF office when necessary). Essential Duties ... Efficiently generate spatial calculations and package geospatial data for deliverable submissions ...

Fullpower Technologies

Data Scientist

Santa Cruz, CA · Remote

$130K - $170K/yr

Fullpower-AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless ... Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in ...

Swish Analytics

Data Scientist

San Francisco, CA · On-site +1

$150K/yr

This position is remote from the USA or Canada. Duties: * Develop infrastructure for trader ... Bachelor's in Data Science, Statistics, Computer Science, Applied Math, or a related technical ...

Federato Technologies

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data scientist on the team working through and building models from scratch that will be pivotal for our ...

Dlapiper

Data Scientist

San Diego, CA · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Dlapiper

Data Scientist

Palo Alto, CA · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Dlapiper

Data Scientist

Los Angeles, CA · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Dlapiper

Data Scientist

San Francisco, CA · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Federato Technologies

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data scientist on the team working through and building models from scratch that will be pivotal for our ...

Swish Analytics

NFL Data Scientist

San Francisco, CA · On-site +1

$140K/yr

Data Science is at the core of our business, so this team has true ownership and impact over ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Swish Analytics

Soccer Data Scientist

San Francisco, CA · On-site +1

$130K/yr

Data Science is at the core of our business, so this team has true ownership and impact over ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

YO AI Labs

AI Data Scientist Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

Golden State

Data Scientist

San Francisco, CA · Remote

$165K/yr

This is full-time remote position. Key Responsibilities * Develop, deploy and monitor predictive ... Maintain a pulse on the current state of data science and basketball analytics * Other duties as ...

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All JobsGeospatial Data Scientist JobsRemote Geospatial Data Scientist JobsRemote Geospatial Data Scientist Jobs in California

Remote Geospatial Data Scientist information

What is a remote geospatial data scientist?

A Remote Geospatial Data Scientist is a professional who analyzes and interprets spatial data, such as maps, satellite imagery, and GPS data, to solve problems or provide insights, all while working from a location outside of a traditional office. They use statistical, mathematical, and programming skills to process large geospatial datasets and often collaborate with teams virtually. Their work can support a variety of industries, including environmental monitoring, urban planning, and logistics, by providing actionable geographic insights. Remote geospatial data scientists commonly use tools like GIS software, Python, and machine learning frameworks. Communication and collaboration tools are also essential for effective remote work.

What are the key skills and qualifications needed to thrive as a remote geospatial data scientist?

To thrive as a Remote Geospatial Data Scientist, you need a strong background in spatial analysis, statistics, and programming, typically supported by a degree in geography, computer science, or a related field. Experience with GIS software (such as ArcGIS or QGIS), remote sensing tools, and programming languages like Python or R is essential, along with familiarity with cloud-based data platforms. Strong problem-solving, self-motivation, and effective communication skills are vital for collaborating remotely and turning complex geospatial data into actionable insights. These skills enable professionals to efficiently interpret and analyze spatial data, deliver valuable solutions, and work effectively within distributed teams.

How do remote geospatial data scientists typically collaborate with multidisciplinary teams across different time zones?

Remote Geospatial Data Scientists often work with professionals in fields like environmental science, urban planning, and software engineering, many of whom may be distributed globally. Effective collaboration relies on clear communication, regular virtual meetings, and the use of shared platforms for data, code, and project management. Flexible scheduling and asynchronous communication tools are key to coordinating across time zones, ensuring that all team members can contribute to project milestones efficiently. Building strong documentation and leveraging collaborative GIS and data platforms further help streamline workflows and maintain project momentum in a remote environment.

What is the difference between Remote Geospatial Data Scientist vs Remote GIS Analyst?

AspectRemote Geospatial Data ScientistRemote GIS Analyst
Required CredentialsBachelor's/Master's in GIS, Geography, Data Science; experience with spatial analysisBachelor's in GIS, Geography, or related field; proficiency in GIS software
Work EnvironmentData analysis, modeling, programming, and spatial data interpretationMapping, data management, spatial data visualization
Employer & Industry UsageTech companies, environmental agencies, urban planningGovernment agencies, utilities, environmental firms
Common Search & ComparisonFocuses on data science and modelingFocuses on mapping and spatial data management

The Remote Geospatial Data Scientist primarily works on advanced spatial data analysis, modeling, and programming to extract insights from geospatial data. In contrast, the Remote GIS Analyst focuses on mapping, data management, and spatial visualization. Both roles require GIS knowledge but differ in their core responsibilities and skill sets.

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

The most popular types of Geospatial Data Scientist jobs in California are:

What are popular job titles related to Remote Geospatial Data Scientist jobs in California?

For Remote Geospatial Data Scientist jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Geospatial Data Scientist jobs in California look for?

The top searched job categories for Remote Geospatial Data Scientist jobs in California are:

What cities in California are hiring for Remote Geospatial Data Scientist jobs?

Cities in California with the most Remote Geospatial Data Scientist job openings:

Remote Geospatial Data Scientist jobs near you
Infographic showing various Remote Geospatial Data Scientist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior Data Scientist

San Francisco, CA • On-site, Remote

Nash, Inc.
See more jobs at Nash, Inc.external

Full-time

Medical, Dental, Vision, PTO

Posted 26 days ago

Job description

Senior Data Scientist
About Nash
Nash is the autonomic logistics platform. We unify decisioning and execution across fleets, carriers, providers, and fulfillment networks, continuously adapting as conditions change and pursuing the best possible outcome for each business.
The world's largest retailers, grocers, and pharmacies, including Walmart, 7-Eleven, Woolworths, and Coles, run critical logistics workflows on Nash. Your work will influence real-world decisions across millions of deliveries.
Nash was founded in 2021 by Mahmoud Ghulman and Aziz Alghunaim. We are backed by Y Combinator, a16z, OpenAI, and other leading investors, and headquartered in San Francisco.
About the role
We are hiring Nash's first Data Scientist. You will combine product judgment, logistics or marketplace expertise, and pragmatic machine learning skills to build data products from discovery through production and measurement.
You will work across pricing, dispatch, carrier selection, ETA prediction, routing, and supply-demand forecasting. This is a high-ownership role for someone who can find valuable problems, turn ambiguity into measurable outcomes, and build the models and systems needed to improve those outcomes in production.
You will partner directly with Product, Engineering, Operations, customers, and company leadership.
What you'll do
  • Identify and scope high-impact opportunities across pricing, cost prediction, dispatch, carrier selection, ETA prediction, routing, and marketplace balancing.
  • Own data science initiatives from 0→1 discovery through 1→10 iteration, deployment, and performance improvement.
  • Work with large, messy operational datasets, including delivery events, geospatial data, carrier performance, customer constraints, and SLA outcomes.
  • Build models that account for real-world logistics constraints, shifting demand, provider availability, and service requirements.
  • Develop production data pipelines and model integrations using Python, SQL, and Snowflake.
  • Partner with engineers to serve models through APIs, batch pipelines, or real-time decision systems.
  • Establish evaluation frameworks, monitoring, experimentation, and A/B testing practices.
  • Measure model performance against business outcomes such as cost, reliability, on-time delivery, and operational intervention.
  • Work directly with enterprise customers to understand their operations and convert business requirements into technical approaches.
  • Communicate findings, tradeoffs, and recommendations clearly to technical and non-technical audiences.

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 research, or another domain with complex real-world constraints.
  • A record of independently taking data science projects from problem definition through production and measurement.
  • Strong proficiency in Python and SQL, with experience working in cloud data warehouses. Snowflake experience is preferred.
  • Experience building and maintaining production machine learning systems. Deep MLOps specialization is not required.
  • Strong product judgment and the ability to connect modeling decisions to customer and business outcomes.
  • Comfort working with incomplete data, ambiguous questions, and changing operational conditions.
  • Clear written and verbal communication, including experience working with customers or senior stakeholders.
  • High agency in a fast-moving environment. You notice valuable problems and act on them.

Bonus
  • Experience with routing, ETA modeling, optimization algorithms, or geospatial data.
  • Familiarity with dispatch systems, carrier networks, logistics marketplaces, or pricing models.
  • Experience with supply-demand forecasting or marketplace balancing.
  • Exposure to dbt, Airflow, or related data orchestration tools.
  • Experience deploying models through APIs or real-time decision systems.
  • Prior experience at an early-stage company or in a founding data role.

Why this role matters
The decisions Nash makes affect what a delivery costs, which resource handles it, when it arrives, and whether the customer's promise holds when conditions change.
As our first Data Scientist, you will define how Nash uses operational data to make those decisions sharper. The models you build will move quickly from analysis into live logistics workflows, giving you a direct view into their customer and business impact.
What you'll love about Nash
  • An early-stage, well-funded company with real revenue and global enterprise customers
  • Significant ownership and autonomy, with direct collaboration with the founders
  • Quarterly team onsites to connect and align in person
  • Competitive compensation and meaningful equity
  • Flexible paid time off
  • Health, dental, and vision insurance

Equal opportunity
At Nash, we believe diverse teams are the strongest teams. We invite applicants of all genders, races, ethnicities, nationalities, ages, religions, sexual orientations, disability statuses, educational experiences, family situations, and socioeconomic backgrounds.
More about Nash
Nash is the platform that powers modern logistics.
Commerce has inverted. For decades, customers came to where products and services were. Now products and services come to them, on their terms, in real time. That shift has turned every company into a logistics company, even though almost none of them were built to be one. Couriers, fleets, gig workers, parcel carriers, in-store labor, and increasingly autonomous systems all have to be coordinated in real time, against tighter windows and rising expectations, with hard-fought customer trust on the line.
Nash unifies decisioning, execution, and capacity into a single programmable platform. Real-time, AI-native intelligence determines what should happen, operational control executes it, and the platform dynamically orchestrates capacity from any source: a company's own fleets, partners, or the Nash delivery network. Whether a job involves a courier, a gig driver, an internal fleet, a store employee, a technician, or an autonomous vehicle, Nash selects the right resource and manages execution through completion.
We power delivery and logistics for some of the most recognizable brands in commerce, including Walmart, Urban Outfitters, 7-Eleven, and Woolworths, alongside platforms like Shopify and Toast. Over the next decade, logistics will become as foundational to commerce as payments, cloud, and connectivity. Nash is the platform that powers it.
Nash was founded in 2021 by Mahmoud Ghulman (2x Founder, MIT) and Aziz Alghunaim (2x Founder, 2x YC, Ex-Palantir, MIT) and is backed by Y Combinator, a16z, and other top investors. We are headquartered in San Francisco.
What You'll Love About Us
• Early-stage, well-funded startup - directly impact the company and grow your career!
• Quarterly broader team on-sites to bond with teammates
• Competitive compensation and opportunity for equity
• Flexible paid time off
• Health, dental, and vision insurance

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