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Spatial Data Science Jobs (NOW HIRING)

We're seeking a Data Scientist who combines technical expertise with strong interpersonal skills to ... science, physics, or a STEM related field Recommended Qualifications * Experience with spatial and ...

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Experience working with geospatial data formats and spatial data processing * Experience supporting scientific or ecosystem modeling workflows preferred * Familiarity with workflow orchestration ...

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Experience working with geospatial data formats and spatial data processing * Experience supporting scientific or ecosystem modeling workflows preferred * Familiarity with workflow orchestration ...

Data Engineer

Houston, TX · On-site

$95K - $130K/yr

Experience working with geospatial data formats and spatial data processing * Experience supporting scientific or ecosystem modeling workflows preferred * Familiarity with workflow orchestration ...

... spatial joins Preferred Qualifications: * Advanced degree in Economics, Data Science, Agricultural Economics, Statistics, Geospatial Science, Applied Mathematics, or Computer Science * Experience ...

... spatial joins Preferred Qualifications: Advanced degree in Economics, Data Science, Agricultural Economics, Statistics, Geospatial Science, Applied Mathematics, or Computer Science Experience with ...

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Spatial Data Science information

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$44.5K

$129.7K

$177.5K

How much do spatial data science jobs pay per year?

As of Jul 1, 2026, the average yearly pay for spatial data science in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 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 GIS jobs pay the most?

Senior GIS analyst, GIS manager, and geospatial data scientist roles tend to offer the highest salaries in the GIS field, often exceeding $80,000 to $100,000 annually depending on experience, location, and industry. These positions typically require advanced skills in GIS software, programming, and data analysis, with certifications like GISP enhancing earning potential.

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.

Can data scientists make $300k?

Data scientists, including those specializing in spatial data science, can earn $300,000 or more at senior levels or in high-demand industries, especially with extensive experience, advanced skills in machine learning, and proficiency in tools like Python or R. Achieving this salary often requires working in large companies, consulting roles, or locations with high living costs, and may involve additional responsibilities or leadership positions.

What does a spatial data scientist do?

A spatial data scientist analyzes geographic data to identify patterns, trends, and relationships using tools like GIS software and programming languages such as Python or R. They develop models, visualize spatial information, and support decision-making in fields like urban planning, environmental management, or logistics.

Is GIS a high demand job?

GIS (Geographic Information Systems) professionals, including those in spatial data science, are in high demand across industries such as urban planning, environmental management, and transportation. The increasing use of spatial analysis, remote sensing, and GIS tools like ArcGIS and QGIS contributes to strong job growth and opportunities for skilled workers.

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.
More about Spatial Data Science jobs
What cities are hiring for Spatial Data Science jobs? Cities with the most Spatial Data Science job openings:
What states have the most Spatial Data Science jobs? States with the most job openings for Spatial Data Science jobs include:
What job categories do people searching Spatial Data Science jobs look for? The top searched job categories for Spatial Data Science jobs are:
Senior Data Scientist - Neuroscience Spatial Multi-omics

Senior Data Scientist - Neuroscience Spatial Multi-omics

MSD

Cambridge, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago


Job description

Job Description

Our Company's Data, AI & Genome Sciences Department in Cambridge, MA is seeking a Senior Specialist (Senior Scientist), Data Science to join the Translational Neuroscience Analytics team and drive integrative analysis of spatial and single-nucleus multi-omics data from patients with neurodegenerative diseases. The qualified individual will be a motivated data scientist or computational biologist with a track record of developing and applying cutting-edge AI/ML methodologies to extract actionable insights from single-nucleus and spatial multi-omics data. In this role, they will leverage spatially resolved transcriptomics data with single-cell resolution to understand target pathway biology in relation to pathological hallmarks of neurodegenerative diseases, especially Alzheimer's disease, and integrate this information with single-nucleus multi-omics data from large patient cohorts to enable causal modeling and prediction of target perturbation effects across cell populations of interest. Through these analyses, they will contribute to the evaluation of specific therapeutic hypotheses as well as the identification and placement of biomarkers along the causal cascade from therapeutic target to clinical outcome, ultimately shaping the translational strategies of our neurodegenerative therapeutic programs. They will work alongside with other data scientists and AI/ML scientists in the department to develop and apply innovative approaches to perform such analyses and further integration with clinical, genetic, and other omics data types. They will also be closely collaborating with cross-functional teams of data scientists, bench biologists, and clinical colleagues to drive our neuroscience biomarker and translational strategies.

Primary responsibilities:

  • Build and deploy analytic workflows leveraging state-of-art computational methods to analyze spatial multi-omics datasets, with a specific focus on target MOA evaluation and biomarker discovery in neurodegenerative diseases.

  • Formulate and drive integration of spatial and single-nucleus multi-omics data to build unified predictive framework capturing the interactions among different CNS cell types (e.g., neurons and microglia).

  • Lead data analytic projects to evaluate therapeutic hypothesis, drive precision biomarker discovery, inform translational strategies, and enable data-driven decision-making of multiple neuroscience drug discovery programs.

  • Collaborate with internal AI/ML teams to develop and incorporate new methodologies into existing frameworks to enhance data analysis capabilities.

  • Work with experimental biologists, functional area experts, and clinical scientists to support drug discovery and development programs at various stages.

  • Provide data science / computational biology input in research strategy, experimental design, provide data analytical input, and assist in interpreting results from both in-vitro and in-vivo studies.

  • Communicate data analytic results effectively to project teams, key stakeholders, as well as the wider scientific community through written and verbal means, including proposals for further experiments, presentations at internal and external meetings, and publications in leading journals.

Required Qualifications:

  • PhD in Data Science, Computational Biology, Computer Science, Genetics/Genomics, Biophysics, Bioinformatics, Statistics, Neuroscience, Neurology, or a related STEM discipline and 0+ years of experience, or an MS and 5+ years of experience.

  • Deep understanding of computational methodologies for single-cell and spatial transcriptomics analysis and extensive experience in their applications, preferably in neurological disorders.

  • Extensive experience in analyzing spatial transcriptomics data with single/sub-cell resolution (e.g., CosMx, Visium HD).

  • Demonstrated expertise in leveraging advanced AI/ML models (e.g., transformers, foundation models) and in silico perturbation simulation.

  • Ability to critically evaluate and apply novel data analysis methods in translational applications.

  • Proficient in one or more programming languages (e.g., Python, R), HPC environments and/or cloud-based platforms, as well as version control systems (e.g., Github).

  • Strong problem-solving skills, self-motivated, attention to detail, and ability to handle multiple projects.

  • Extensive experience to conduct research in a collaborative environment and excellent ability to communicate scientific questions, methodologies, findings and insights.

  • Proven track record (e.g., peer-reviewed publications) of extracting actionable insights from analysis of spatial/single-cell omics data.

Preferred Qualifications:

  • Outstanding scientific caliber with strong capabilities to identify key analytic questions and formulate rigorous data analytic plans to address critical scientific needs of drug discovery programs.

  • Good understanding of neurobiology, particularly neurodegenerative diseases.

  • Familiarity with large public single-nucleus multi-omics datasets from neurodegenerative disease patient cohorts (e.g, ROSMAP, SEA-AD).

  • Additional 2+ years of multi-omics data analytics experience post final degree is preferred.

#EligibleforERP

Required Skills:

Alzheimer's Disease, Computational Biology, Computer Science, Cross-Team Collaboration, Database Design, Data-Driven Decision Making, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning (ML), MultiModal AI, Neurodegenerative Diseases, Neuroscience, Omics, Programming Languages, Single Cell Analysis, Single-Cell Genomics, Spatial Data Analysis, Stakeholder Relationship Management, Teamwork, Transcriptomics

Preferred Skills:

Foundation Model Fine Tuning, Foundation Models, Transformer Model

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another's thinking and approach problems collectively.

Learn more about your rights, including under California, Colorado and other US State Acts

The salary range for this role is

$144,800.00 - $227,900.00

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 relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.

You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.

San Francisco Residents Only:We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only:We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance

Search Firm Representatives Please Read Carefully
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status:

Regular

Relocation:

Domestic

VISA Sponsorship:

Yes

Travel Requirements:

No Travel Required

Flexible Work Arrangements:

Hybrid

Shift:

Not Indicated

Valid Driving License:

No

Hazardous Material(s):

n/a

Job Posting End Date:

07/10/2026

*A job posting is effective until 11:59:59PM on the day BEFOREthe listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.