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Geospatial Data Scientist Jobs in New York (NOW HIRING)

Bedrock Robotics

Data Scientist

New York, NY · On-site

Bedrock Robotics is hiring a Data Scientistto lead high-impact data science work across autonomy ... geospatial systems, computer vision outputs, IoT, ad-tech, or large-scale consumer platforms)

Urban SDK

Data Engineer

Manhattan, NY · On-site +1

$126K - $151K/yr

Manage large-scale geospatial and temporal datasets stored in AWS S3. Collaborate with data scientists to productionize machine learning models and ensure smooth data availability. Implement data ...

Urban SDK

Data Engineer

Manhattan, NY · On-site +1

$126K - $151K/yr

Manage large-scale geospatial and temporal datasets stored in AWS S3. Collaborate with data scientists to productionize machine learning models and ensure smooth data availability. Implement data ...

YO AI Labs

GIS/Geospatial Expert

New York, NY · Remote

... 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 ...

City of New York

Data Scientist, RIS

Manhattan, NY · On-site +1

NYC DOT seeks to hire a Data Scientist to join the Data Operations, Systems, and Analytics (DOSA ... Proven track record of conducting quantitative and/or geospatial research. Work Location: 55 Water ...

City of New York

Data Scientist, RIS

Manhattan, NY · On-site +1

NYC DOT seeks to hire a Data Scientist to join the Data Operations, Systems, and Analytics (DOSA ... Proven track record of conducting quantitative and/or geospatial research. Work Location: 55 Water ...

Keylent Inc

ETL Developer / AbInitio

Manhattan, NY · On-site

$56.25 - $73.50/hr

This role involves leading the design and implementation of geospatial data solutions, ensuring ... Science, Information Technology, or a related field • Ability to manage multiple tasks and ...

T-Mobile

Senior Applied Scientist

New York, NY · On-site

$116K - $210K/yr

You'll collaborate with engineers, data scientists, product managers, and other stakeholders to ... Experience in AdTech and GIS or geospatial data processing is a plus. * At least 18 years of age

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $184K/yr

Collaborate with computational ecologists and data scientists to integrate generative design with ... Utilize inferred geospatial data to drive the computational synthesis and design of functional ...

City of New York

Program Data Scientist

Queens, NY · On-site

$125K - $150K/yr

... QGIS, geospatial Python libraries). -Experience designing analyses or data systems for tracking ... CITY RESEARCH SCIENTIST - 21744 Qualifications 1. For Assignment Level I (only physical, biological ...

City of New York

Program Data Scientist

Queens, NY · On-site

... QGIS, geospatial Python libraries). - Experience designing analyses or data systems for tracking ... CITY RESEARCH SCIENTIST - 21744 Qualifications 1. For Assignment Level I (only physical, biological ...

City of New York

Program Data Scientist

Queens, NY

... QGIS, geospatial Python libraries). - Experience designing analyses or data systems for tracking ... CITY RESEARCH SCIENTIST - 21744 Qualifications 1. For Assignment Level I (only physical, biological ...

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All JobsGeospatial Data Scientist JobsGeospatial Data Scientist Jobs in New York

Geospatial Data Scientist information

See New York salary details

$41K

$134.3K

$215K

How much do geospatial data scientist jobs pay per year?

As of Sep 4, 2026, the average yearly pay for geospatial data scientist in New York is $134,280.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,800.00 and $148,800.00 per year, depending on experience, location, and employer.

What is a geospatial data scientist?

A Geospatial Data Scientist analyzes spatial and geographic data to extract insights, create predictive models, and support decision-making. They use tools like GIS, remote sensing, machine learning, and statistical analysis to process location-based data. Their work spans various industries, including urban planning, environmental monitoring, agriculture, and logistics. By leveraging spatial data, they help optimize operations, manage resources, and solve complex geographic problems.

What does a geospatial data scientist do?

As a Geospatial Data Scientist, your daily tasks often involve collecting, cleaning, and analyzing spatial datasets using GIS tools and programming languages. You may be responsible for developing spatial models, visualizing geographic data through interactive maps, and generating reports to help guide strategic decisions. Collaboration with professionals from engineering, urban planning, or environmental science teams is common, requiring you to communicate complex analyses in a clear and actionable manner. Additionally, you might participate in project meetings to align your work with organizational goals and stakeholder needs. This dynamic role blends technical analysis with communication and teamwork, making each day varied and intellectually stimulating.

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

Geospatial Data Scientists require expertise in spatial analysis, statistics, and data modeling, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), programming languages like Python or R, and familiarity with spatial databases are often expected, while certifications in GIS can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills help professionals translate complex data into actionable insights and work well with diverse teams. Mastery of these skills ensures accurate geospatial analyses and supports informed, data-driven decision making in various industries.

How much does a geospatial data scientist make?

A geospatial data scientist's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, location, and industry. Senior roles or those with specialized skills in GIS tools and programming may earn higher compensation.

Is geospatial data scientist still in demand?

Yes, geospatial data scientists are in high demand due to the increasing use of geographic information systems (GIS), remote sensing, and spatial analysis across industries such as urban planning, environmental management, and transportation. The role often requires skills in programming, data analysis, and tools like Python, R, and GIS software, with strong job growth projected in the coming years.

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

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

What are popular job titles related to Geospatial Data Scientist jobs in New York?

For Geospatial Data Scientist jobs in New York, the most frequently searched job titles are:

What job categories do people searching Geospatial Data Scientist jobs in New York look for?

The top searched job categories for Geospatial Data Scientist jobs in New York are:

What cities in New York are hiring for Geospatial Data Scientist jobs?

Cities in New York with the most Geospatial Data Scientist job openings:

Geospatial Data Scientist jobs near you
Infographic showing various Geospatial Data Scientist job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $134,280 per year, or $64.6 per hour.

Data Scientist - Visualization (Power BI)

Conch Technologies Inc

New York, NY • On-site

Contractor

Re-posted 5 days ago

Job description

 
Job Title: Data Scientist – Visualization (Power BI)

Location: Remote (Must be able to work EST hours)
Employment Type: 6+ Months
Interview Process: Immediate interviews available

Job Summary

We are seeking an experienced Data Scientist – Visualization with strong expertise in Power BI to join a growing analytics and data science team. The ideal candidate will have a proven background in data science, advanced analytics, machine learning, data visualization, and scalable data pipeline development. This role requires a combination of technical expertise, business acumen, and the ability to transform complex data into actionable insights for both technical and non-technical stakeholders.

Power BI expertise is required. Experience with Power Apps is a plus.

Key Responsibilities
  • Design, build, and maintain scalable and reusable data pipelines that integrate structured, unstructured, geospatial, LiDAR, and real-time data from multiple sources.
  • Develop and deploy advanced analytical, statistical, and predictive models including machine learning, time-series forecasting, causal inference, and geospatial analytics.
  • Create and operationalize interactive dashboards, visualizations, and analytical interfaces using Power BI and other visualization platforms.
  • Translate complex analytical findings into meaningful business insights and recommendations.
  • Lead the development of innovative data-driven products and solutions by collaborating with business stakeholders and technical teams.
  • Perform exploratory data analysis, feature engineering, model development, validation, deployment, and monitoring.
  • Build and optimize data transformation workflows supporting digital delivery and operational programs.
  • Establish and promote best practices in data science, analytics, visualization, model governance, and responsible AI.
  • Drive knowledge sharing and technical leadership across teams and business units.
  • Collaborate with clients and internal stakeholders to define requirements, scope projects, and deliver impactful analytical solutions.
Required QualificationsEducation
  • Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Geography, or a related quantitative field with 5+ years of experience; OR
  • Bachelor’s degree with 10+ years of relevant experience.
Experience
  • 10+ years of hands-on experience in data science, analytics engineering, machine learning, and advanced analytics.
  • 5+ years of client-facing consulting or solution delivery experience.
  • Proven experience delivering analytics solutions from concept through production deployment.
Technical Skills
  • Strong expertise in Power BI for dashboard development, visualization, reporting, and data storytelling.
  • Experience with Power Apps is preferred.
  • Advanced Python programming experience using Pandas, NumPy, SciPy, Polars, and related libraries.
  • Strong SQL and data modeling expertise.
  • Experience with R programming.
  • Deep knowledge of machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, and Statsmodels.
  • Experience with time-series forecasting, predictive analytics, feature engineering, and statistical modeling.
  • Strong geospatial analytics experience using ArcGIS, GeoPandas, PostGIS, GDAL/OGR, PDAL, or similar technologies.
  • Experience building and deploying solutions on Azure, AWS, or GCP.
  • Knowledge of MLOps practices including CI/CD, containerization, model monitoring, experiment tracking, and deployment automation.
  • Experience with Tableau, Plotly/Dash, or other visualization platforms is a plus.
Preferred Qualifications
  • Experience within transportation, aviation, construction, engineering, infrastructure, or facilities operations.
  • Exposure to BIM, VDC, digital twins, IoT, telemetry, or operational technology systems.
  • Experience working with LiDAR, imagery, sensor data, and geospatial datasets.
  • Familiarity with foundation models, multimodal AI, and advanced analytics applications.
  • Experience with product incubation, innovation initiatives, or startup methodologies.
  • Strong understanding of responsible AI, model explainability, governance, and regulatory compliance.
Key Competencies
  • Exceptional analytical and problem-solving abilities.
  • Strong communication and presentation skills.
  • Ability to explain complex technical concepts to business stakeholders.
  • Leadership mindset with experience mentoring teams and driving best practices.
  • Self-starter capable of working independently in a fast-paced environment.