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Spatial Data Science Jobs in Fremont, CA (NOW HIRING)

The 10x platform generates the single‑cell and spatial data that AI and data partners need at ... Scientific and technical fluency in genomics, single‑cell, spatial biology, and NGS, enough to ...

Collaborate cross-functionally with frontend and AI/data science to expose clean, structured data ... Familiarity with geographic/spatial data processing and mapping APIs. * Basic understanding of ...

... spatial data technologies. * Proven ability to resolve complex production-level issues and optimize system performance. Education: * Bachelor's degree in computer science, computer information ...

... spatial data technologies. * Proven ability to resolve complex production-level issues and optimize system performance. Education: * Bachelor's degree in computer science, computer information ...

... spatial data technologies. * Proven ability to resolve complex production-level issues and optimize system performance. Education: * Bachelor's degree in computer science, computer information ...

Showing results 21-40

Spatial Data Science information

See Fremont, CA salary details

$48.7K

$142K

$194.3K

How much do spatial data science jobs pay per year?

As of Aug 12, 2026, the average yearly pay for spatial data science in Fremont, CA is $141,996.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,300.00 and $150,500.00 per year, depending on experience, location, and employer.

What is spatial data science?

Spatial data science is a field that combines data science techniques with geographic information systems (GIS) to analyze and interpret spatial or location-based data. It involves collecting, processing, and visualizing data that has a geographic or spatial component, such as maps, satellite images, or GPS coordinates. Spatial data scientists use methods from statistics, machine learning, and computer science to solve problems related to urban planning, environmental monitoring, transportation, and more. The insights gained from spatial data science help organizations make better decisions based on the relationships and patterns found in geographic data.

What are the key skills and qualifications needed to thrive as a spatial data scientist, and why are they important?

To thrive as a Spatial Data Scientist, you need a strong background in statistics, geospatial analysis, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases (like PostGIS), and relevant certifications (e.g., Esri Technical Certification) is commonly required. Strong analytical thinking, problem-solving abilities, and effective communication are vital soft skills to interpret spatial data and convey insights to stakeholders. These competencies are crucial for extracting actionable insights from complex geospatial datasets and supporting informed decision-making.

What is the difference between Spatial Data Science vs Geospatial Analyst?

AspectSpatial Data ScienceGeospatial Analyst
Required CredentialsDegree in GIS, Geography, Data Science, or related fields; often includes certifications in GIS or data analysisDegree in Geography, GIS, or related fields; certifications in GIS software are common
Work EnvironmentData analysis, modeling, and programming; often in tech or research settingsMapping, data visualization, and GIS software use; typically in government, environmental, or urban planning agencies
Employer & Industry UsageTech companies, research institutions, urban planning, environmental agenciesGovernment agencies, environmental consultancies, urban planning firms

Spatial Data Science focuses on analyzing spatial data using advanced data science techniques, programming, and modeling. In contrast, Geospatial Analysts primarily work with GIS software to create maps and visualize spatial data. While both roles require GIS knowledge, Spatial Data Scientists often have stronger programming and statistical skills, working on complex data analysis projects, whereas Geospatial Analysts focus more on mapping and data visualization tasks.

What are some typical challenges spatial data scientists face when integrating geospatial data from multiple sources?

Spatial data scientists often encounter challenges like inconsistencies in data formats, varying coordinate reference systems, and differences in spatial resolution when integrating geospatial data from multiple sources. Addressing these requires familiarity with data transformation tools and a strong understanding of spatial data standards. Additionally, ensuring data quality and managing large datasets can be complex, so attention to detail and effective use of GIS software are crucial for successful integration.
What job categories do people searching Spatial Data Science jobs in Fremont, CA look for? The top searched job categories for Spatial Data Science jobs in Fremont, CA are:
What cities near Fremont, CA are hiring for Spatial Data Science jobs? Cities near Fremont, CA with the most Spatial Data Science job openings:
Infographic showing various Spatial Data Science job openings in Fremont, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $141,996 per year, or $68.3 per hour.

Head of Strategic Partnerships

Neara

Pleasanton, CA • On-site

$305 - $412.60/hr

Other

Medical, Retirement

Posted 4 days ago


Job description

About the Role

The Head of Strategic Partnerships is responsible for driving long‑term commercial revenue for 10x Genomics through structured, multi‑year partnerships rather than transactional volume. You will identify, secure, and expand the highest‑value opportunities across the 10x portfolio, design the partnership terms and business case needed to close them, and then own and grow the relationships over time. You will do this in close partnership with cross‑functional teams and the executive leadership, bringing them in where shared ownership advances the deal.

The emphasis sits across three connected areas: partnerships across the AI ecosystem, large‑scale data generation for AI and virtual cell and tissue models, and population‑scale studies. These initiatives share a common thread. The 10x platform generates the single‑cell and spatial data that AI and data partners need at scale, and that data increasingly feeds AI‑driven drug discovery and development. This role turns that data into durable commercial value across both the AI ecosystem and biopharma. You will also work on other complex, high‑value relationships that span regions and require a tailored business case, including agreements that go beyond standard catalog pricing. The work splits roughly evenly between business development and market development. You will build awareness and demand across the AI and biopharma ecosystem while sourcing and closing deals, some of which will land early. You will own and grow many of the largest partnerships you put in place, pulling in others for shared ownership as deals mature.

Candidates should be self‑starters, creative deal‑makers, and strategic thinkers who are comfortable moving quickly, managing several priorities at once, and communicating credibly with every level of the organization.

What you will be doing
  • Map and prioritize target partners across the AI and biopharma ecosystem, alongside the key strategic accounts and institutions that anchor them. Build and formalize a tracking and engagement plan for the highest‑value relationships.
  • Lead market development. Build awareness and demand ahead of the deals, including:
    • Growing the case for single‑cell and spatial data in biopharma AI and drug development, and helping shape how that emerging category is defined.
    • Developing and nurturing key opinion leaders whose adoption and advocacy move the market, and turning those relationships into pipeline.
  • Drive commercial partnership strategy. Develop the short‑ and long‑term strategy to advance 10x's position against key initiatives, with a focus on:
    • Partnering across the organization to capture large commercial, research, and translational opportunities and collaborations.
    • Translating customer needs back to internal teams and feeding them into platform and product prioritization.
  • Build the commercial framework for partnerships. Define ideal partnership terms, lifetime value modeling, and the target partners for each initiative.
  • Source, structure, and close deals. Negotiate agreements that create value against 10x's strategic and financial objectives, working across Legal, Finance, Marketing, Sales, and R&D. Bring clarity to who is responsible, accountable, consulted, and informed on each partnership.
  • Own and grow the partnerships you build. Manage the largest strategic relationships post‑signing, working with Sales and Marketing to deepen them and expand within the surrounding ecosystem.
  • Work with the senior leadership team to triage inbound partnership opportunities, assess fit, and decide where to invest.
Minimum Requirements
  • A track record of structuring and closing large, complex, multi‑year commercial deals, not transactional orders.
  • An advanced degree in genetics, genomics, or a related field, and/or an MBA, with 5+ years in the life sciences, genomics, or biopharmaceutical industries.
  • Fluency in the AI and data ecosystem as it applies to biology. You understand how frontier labs, infrastructure providers, and data partners think about models, compute, and data access, and you can build a commercial relationship with a technical, AI‑driven partner rather than only a traditional life sciences buyer. This includes familiarity with data licensing and with how large‑scale data is used to train models, including virtual cell and tissue models.
  • Understanding of drug discovery and development, including how AI and multiomic data feed drug programs and where commercial value is created across the pipeline. Large biopharma business development experience is a strong asset.
  • Market development experience. A record of creating and growing demand in new or emerging categories, not just closing in established markets. The population‑studies and AI efforts both require building a market, not selling into existing budgets.
  • Scientific and technical fluency in genomics, single‑cell, spatial biology, and NGS, enough to hold credibility with both research and commercial counterparts.
  • Experience with population‑scale genomics (national genome programs, biobanks, or large cohort studies) and with grant‑funded or public‑private consortia and their funding mechanisms is strongly preferred.
  • Creativity in deal design. The ability to build commercial structures that do not yet exist for opportunities outside the standard playbook.
  • Strong analytical, project management, and organizational skills, with sound business judgment.
  • Strong collaboration and communication skills, shown by working cross‑functionally and championing a business case with senior management.
  • A strategic thinker who can help set direction and define the strategy and tactics to drive growth.
  • An energetic, resourceful self‑starter with high integrity and executive presence, comfortable in a fast‑moving, entrepreneurial environment.
  • Flexibility to travel up to 40%.
  • Please submit a deal sheet along with your resume.
Compensation and Benefits

Pay Range: $305,000—$412,600 USD. Base pay is one component of the total compensation package. The role is also eligible for equity grants, comprehensive health and retirement benefits, and an annual bonus program or sales incentive program. Hiring process details will be shared by a recruiter.

Equal Opportunity Employer

Individuals seeking employment at 10x Genomics are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation, or any other characteristic protected by applicable law.

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