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Geospatial Data Science Jobs in Connecticut (NOW HIRING)

ISO New England, Inc.

Data Scientist

Windsor, CT · On-site

$117K - $146K/yr

Experience working with big data, geospatial analytics, and/or probabilistic forecasting * Experience building applications that ingest and use data from multiple sources and formats (i.e., data ...

Iberdrola

Senior Analyst - GIS

East Hartford, CT · On-site

... for geospatial data. 5% Required Qualifications * Must have experience with computers, printers ... A bachelor's degree in Geography, Engineering or Computer Science with at least 4 or more years of ...

Xylem

Hydroinformatics Engineer

South Windsor, CT

Experience with modern data science workflows for data access and filtering, geospatial analysis, and model parameter estimation. * Excellent verbal and written communication skills. * Self-motivated ...

All JobsGeospatial Data Science JobsGeospatial Data Science Jobs in Connecticut

Geospatial Data Science information

See Connecticut salary details

$20.9K

$73.7K

$116.1K

How much do geospatial data science jobs pay per year?

As of Jun 22, 2026, the average yearly pay for geospatial data science in Connecticut is $73,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,800.00 and $76,100.00 per year, depending on experience, location, and employer.

How does a Geospatial Data Scientist typically collaborate with other departments or teams within an organization?

Geospatial Data Scientists often work closely with professionals from diverse departments such as urban planning, environmental science, IT, and business analytics. Collaboration usually involves sharing spatial insights, integrating geospatial data with other datasets, and contributing to interdisciplinary projects that require spatial analysis or mapping. Effective communication is crucial, as you'll translate complex geospatial findings into actionable recommendations for non-technical stakeholders. This cross-functional teamwork not only broadens your understanding of organizational goals but also enhances the impact and visibility of geospatial analyses.

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

AspectGeospatial Data ScienceGIS Analyst
Required CredentialsDegree in Data Science, Geography, or related; often includes programming skillsDegree in Geography, GIS, or related; GIS certifications common
Work EnvironmentData analysis, modeling, programming, often in tech or research settingsMapping, spatial data management, using GIS software in various industries
Employer & Industry UsageTech companies, research institutions, government agencies focusing on spatial data analysisUrban planning, environmental agencies, utilities, and government agencies

While both roles work with spatial data, Geospatial Data Science emphasizes data analysis, modeling, and programming skills to extract insights from geospatial data. GIS Analysts focus more on mapping, data management, and using GIS software for spatial analysis. The roles often overlap but differ mainly in technical focus and application areas.

What are the key skills and qualifications needed to thrive as a Geospatial Data Scientist, and why are they important?

To thrive as a Geospatial Data Scientist, you need a solid background in statistics, spatial analysis, and programming, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), spatial databases, and coding languages like Python or R is essential, and certifications in GIS can be advantageous. Strong problem-solving skills, attention to detail, and effective communication help translate complex spatial data into actionable insights for diverse stakeholders. These skills ensure accurate data analysis, innovative solutions, and impactful decision-making in fields reliant on geographic information.

What is geospatial data science?

Geospatial data science is an interdisciplinary field that focuses on analyzing and interpreting data that has a geographic or spatial component. It combines techniques from data science, statistics, and geographic information systems (GIS) to extract insights, identify patterns, and solve problems related to location-based data. Professionals in this field work with mapping, remote sensing, spatial analysis, and visualization tools to support decision-making in areas like urban planning, environmental monitoring, and logistics.
What are popular job titles related to Geospatial Data Science jobs in Connecticut? For Geospatial Data Science jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Science jobs in Connecticut look for? The top searched job categories for Geospatial Data Science jobs in Connecticut are:
Geospatial Data Science jobs near you
Infographic showing various Geospatial Data Science job openings in Connecticut as of June 2026, with employment types broken down into 1% As Needed, 85% Full Time, 3% Part Time, 2% Temporary, 8% Contract, and 1% Nights. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $73,719 per year, or $35.4 per hour.
Data Scientist

Data Scientist

ISO New England, Inc.

Windsor, CT • On-site

$117K - $146K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Job description

ISO New England is the independent system operator responsible for ensuring the safe and reliable flow of electricity in our region and planning for the future of the electric grid. We are at the forefront of New England's ongoing transition to clean energy.
New technologies and the New England region's economy-wide decarbonization efforts are driving a profound transformation in the work of the Forecast Group within System Planning. Responsible for analytics and predictive modeling of the region's electricity demand across all timescales-spanning both short-term and long-term time horizons-the Forecast Group is innovating and redesigning its forecasting methods, software, and tools to meet changing trends in how retail customers procure, manage and use electricity.
This role requires a self-starter with demonstrated ability to work seamlessly both unsupervised and in a fast-paced, collaborative team environment. This position will be focused on long-term forecasting, with potential opportunities to work in long-range forecasting as well. The candidate will have an opportunity to lead the team's development of next generation forecasting tools that are integral to the planning and operation of the future grid.
What we offer you:
  • A stable, mission-driven workplace where your impact truly matters
  • A highly engaged work environment that values inclusion, collaboration, and employee safety and wellbeing
  • Competitive compensation with a base salary + performance bonus
  • Robust benefits package, including:
    • Enhanced 401(k) and financial planning support
    • Tuition reimbursement and professional development
    • Wellness programs, including an onsite gym
    • Flexible work hours
    • Employee Business Networks
    • Onsite luncheon spaces with free coffee and a variety of dining options
  • Hybrid work environment (3 days/week onsite)
  • Distance-based relocation assistance available

How you will make an Impact
  • Work independently and collaboratively on analytical, programming, modelling, and data management activities
  • Map out and document problem statements, project requirements and associated workflows in pursuit of efficient and effective solutions
  • Leverage a curious mindset, initiative, and "elbow grease" to enhance existing processes, and to innovate new forecasting methods, tools, and software
  • Communicate complex, technical content to a diverse audience through written reports and presentations
  • Apply a persistent drive for quality results to lead the development of data pipelines, reusable software packages and visualizations
  • Stay current with forecasting research and industry best practices; evaluate and implement relevant approaches strategically

What we are looking for
  • Bachelor's degree in Economics, Mathematics, Engineering, Operations Research, or a related field
  • 3+ years of experience in the energy industry in forecasting, data analytics, or equivalent
  • Proficiency in at least one advanced programming language such as Python, R, MATLAB, or SAS
  • Hands-on experience developing software in a collaborative team environment
  • Experience working with big data, geospatial analytics, and/or probabilistic forecasting
  • Experience building applications that ingest and use data from multiple sources and formats (i.e., data wrangling/data munging).
  • 5+ years of relevant experience is required to be considered for a senior-level position. 7+ years of relevant experience is required to be considered for a lead-level position.
  • Excellent written and verbal communication skills
  • Desired but not required:
    • Experience in electricity consumption modelling or economic modelling in the energy sector
    • Knowledge about distributed energy resources (e.g. photovoltaics, batteries), electric vehicles, and/or cold-climate heat pumps

This employer will not sponsor applicants for work visas for this position (ex: H-1B, F-1/CPT/OPT, O-1, E-3, TN, J, etc.).
The expected salary range for the Associate to Mid-Level is $86,000 - $120,000 per year. We will also consider a Senior or Lead. The pay range for the Senior to Lead level is $117,000 - $146,000 annually. This role is also eligible for an annual performance bonus, comprehensive health insurance (medical, dental and vision), flexible spending and health savings accounts, a 401(k) plan with generous employer contributions and a student debt benefit, life and AD&D insurance, disability insurance, critical illness and hospital indemnity benefits, paid time off, paid leave, a wellness program, an employee assistance program and other great company perks.
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This is a U.S. based role. If the successful candidate resides outside of the U.S., relocation will be required.
Equal Opportunity: We are proud to be an EEO employer. Applicants for employment are considered without regard to race, color, religion, creed, sex (including pregnancy, childbirth, and related medical conditions), gender identity or expression, sexual orientation, citizenship, national origin, age, ancestry, marital status, disability (including learning, mental, intellectual, and physical), service in the uniformed services, genetic information, or any other status protected by applicable law.
Drug Free Environment: We maintain a drug-free workplace and perform pre-employment substance abuse testing.

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