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Data Scientist Jobs in Vermont (NOW HIRING)

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Data Scientist information

See Vermont salary details

$39.9K

$130.5K

$208.9K

How much do data scientist jobs pay per year?

As of Aug 24, 2026, the average yearly pay for data scientist in Vermont is $130,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,700.00 and $144,600.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What do data scientists do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

What are some typical projects data scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and employment opportunities continue to grow as organizations seek to leverage big data for competitive advantage.

What does a data scientist do exactly?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use statistical techniques, programming languages like Python or R, and tools such as SQL and machine learning algorithms to interpret data and solve complex problems.

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

The most popular types of Data Scientist jobs in Vermont are:

What are popular job titles related to Data Scientist jobs in Vermont?

For Data Scientist jobs in Vermont, the most frequently searched job titles are:

What job categories do people searching Data Scientist jobs in Vermont look for?

The top searched job categories for Data Scientist jobs in Vermont are:

What cities in Vermont are hiring for Data Scientist jobs?

Cities in Vermont with the most Data Scientist job openings:

What are popular job titles related to Data Scientist jobs in VT?

For Data Scientist jobs in VT, the most frequently searched job titles are:

Infographic showing various Data Scientist job openings in Vermont as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $130,502 per year, or $62.7 per hour.

AI/ML Ecosystem Data Analyst

The University of Vermont

Burlington, VT • On-site

$80K - $95K/yr

Full-time

Posted 4 days ago


University Of Vermont rating

8.1

Company rating: 8.1 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

168th of 622 rated colleges and universities


Job description

AI/ML Ecosystem Data Analyst
Posting Summary
Serve as the AI/ML Ecosystem Data Analyst within the USGS Research Cooperative Unit at UVM ,and in collaboration with the Spatial Analysis Lab ( SAL ). The primary role of this position is to analyze ecological data and design, build, and operationalize AI/ML workflows that collect, process, and derive insight from heterogeneous data sources, including wildlife imagery, bioacoustics recordings, geospatial and remotely sensed data, sensor networks, and field observations. Develop, train, evaluate, and deploy AI/ML models for mapping, classification, and detection of wildlife and other features, and build the data pipelines, databases, and R Shiny or comparable interfaces that make results reproducible, maintainable, and accessible to researchers, partners, and the public. Support the AI/ML branch of RSENR within the Cooperative Unit and SAL , contribute to ecosystem monitoring efforts, and help oversee the Alliance for Monitoring Biodiversity and Ecosystems Remotely ( AMBER ) program. Work under the direction of the USGS Research Cooperative Unit Leader and collaborate with the SAL Director, RSENR , and other partners on grant writing, business development, and research initiatives, while independently pursuing outside funding opportunities. Partner with geospatial analysts and the development team lead on research and development of new AI/ML methods and models
Minimum Qualifications (or equivalent combination of education and experience)
- PhD in Computer Science, Wildlife Biology, Ecology, Data Science, Bioinformatics, or a closely related discipline, and four years related professional experience.
- Demonstrated expertise in data science, machine learning, and AI applications.
- Strong proficiency in relational database design and management, including stand-alone programs such as SQLite and served databases such as SQL or Postgres.
- Experience with APIs, web services, Power Automate, Teams, and Sharepoint for workflow integration.
- Strong record of interdisciplinary collaboration and scientific productivity.
- Experience managing complex technical or research projects, including grant writing.
- Experience with cloud-native infrastructure and scalable AI workflows, focused primarily on the R and Python coding languages.
- Substantial experience in working with the public and agency monitoring partners.
Desirable Qualifications
- Postdoctoral experience preferred
- High proficiency in public outreach and instruction desired
- Supervisory or personnel management experience desired
Anticipated Pay Range
$80,000 - $95,000
Other Information
Special Conditions
A probationary period may be required, Contingent on continued funding, Occasional evening and/or weekends required (if non-exempt position, may result in overtime), Travel to and from worksites required, This position is eligible for a hybrid schedule with an option to split time between campus and elsewhere, in accordance with the university telecommuting policy, Background Check required for this position

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