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Entry Level Environmental Data Scientist Jobs in Jordan, NY

Arcadis

Environmental Engineer

Syracuse, NY · Hybrid

Arcadis is seeking an entry-level Environmental Engineer to join our team in Syracuse, NY. This ... You will work alongside Senior Scientists, Project/Program Managers, and Technical Experts on ...

Arcadis

Environmental Engineer

Syracuse, NY · On-site

Arcadis is seeking an entry-level Environmental Engineer to join our team in Syracuse, NY. This ... You will work alongside Senior Scientists, Project/Program Managers, and Technical Experts on ...

SynergisticIT

Junior ML Engineer (Remote)

Syracuse, NY · On-site

We are continuously looking for entry-level software programmers, Java full stack developers, Python/Java developers, data analysts/data scientists, data engineers, machine learning engineers for ...

SynergisticIT

Java/C++ Developer - Junior/Entry

Syracuse, NY · On-site

$66.20K - $86K/yr

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

INFICON

Associate Research Scientist

East Syracuse, NY · On-site

... and environmental health and safety. The Associate Research Scientist role is a key contributor ... Data Collection, Processing & Analysis You will gather, process, and analyze experimental results ...

INFICON

Associate Research Scientist

East Syracuse, NY · On-site

... and environmental health and safety. The Associate Research Scientist role is a key contributor ... Data Collection, Processing & Analysis You will gather, process, and analyze experimental results ...

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Entry Level Environmental Data Scientist information

See Jordan, NY salary details

$41.1K

$84.3K

$123.2K

How much do entry level environmental data scientist jobs pay per year?

As of May 27, 2026, the average yearly pay for entry level environmental data scientist in Jordan, NY is $84,273.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,100.00 and $98,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Environmental Data Scientist, and why are they important?

To thrive as an Entry Level Environmental Data Scientist, you need a background in environmental science or a related field, along with strong skills in data analysis and statistics. Familiarity with programming languages like Python or R, experience with GIS software, and knowledge of data visualization tools are typically required. Analytical thinking, attention to detail, and effective communication are valuable soft skills that help in interpreting and sharing complex findings. These competencies are crucial for generating reliable insights and informing environmental decision-making within organizations.

What types of projects and data sets do entry-level environmental data scientists typically work with?

As an entry-level environmental data scientist, you will often work with diverse data sets such as air and water quality measurements, climate records, satellite imagery, and GIS data. Projects can include analyzing trends in pollution, modeling the effects of environmental policies, or creating data visualizations to support sustainability initiatives. You’ll collaborate closely with environmental engineers, researchers, and policy teams, often participating in both data cleaning and preliminary analysis before results are shared with stakeholders. This variety provides valuable exposure to real-world environmental issues and lays a solid foundation for career growth.

What does an Entry Level Environmental Data Scientist do?

An Entry Level Environmental Data Scientist collects, analyzes, and interprets environmental data such as air, water, and soil quality. They use statistical methods and programming tools to help identify patterns and trends, supporting research and policy decisions. Often, they work under the guidance of senior scientists to prepare reports, visualize data, and ensure data quality. Their work helps organizations understand environmental impacts and develop solutions for sustainability.

What is the difference between Entry Level Environmental Data Scientist vs Entry Level Environmental Analyst?

AspectEntry Level Environmental Data ScientistEntry Level Environmental Analyst
Required CredentialsBachelor's in Environmental Science, Data Science, or related field; some roles may prefer certifications in data analysis or GISBachelor's in Environmental Science, Environmental Management, or related field; certifications in environmental regulations or GIS are common
Work EnvironmentData-focused roles often in labs, research institutions, or corporate sustainability teamsFieldwork, data collection, and reporting in government agencies, consulting firms, or NGOs
Employer & Industry UsageUsed in research, corporate sustainability, and environmental consultingCommon in government agencies, environmental consulting, and non-profit organizations

While both roles require a background in environmental sciences, the Environmental Data Scientist focuses more on data analysis, modeling, and programming, whereas the Environmental Analyst emphasizes data collection, reporting, and regulatory compliance. Understanding these differences helps job seekers target the right roles based on their skills and career goals.

What cities near Jordan, NY are hiring for Entry Level Environmental Data Scientist jobs? Cities near Jordan, NY with the most Entry Level Environmental Data Scientist job openings:
Entry Level Environmental Data Scientist jobs near you
Data Scientist

Data Scientist

Zimmerman Advertising

Skaneateles Falls, NY • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

The Data Scientist works closely with Retail Technology, Media and Account Services teams to provide predictive modeling of Marketing, Direct & Digital Efforts. We are looking for a motivated Data Scientist and analytical thought leader. This is a rare opportunity to be part of a diverse and newly expanded analytics department and a great fit for a predictive modeler with a desire to impact business results.

Responsibilities:

  • Responsible for assisting the Lead Data Scientist and the data science team with building solution accelerators, pipeline development, and building integrations with our LLM Products on the Databricks platform
  • Using ML flow or similar application to create and serve up ML Models
  • Collaborate with cross-functional teams, including data scientists, product managers, data engineers, and software engineers, to design, develop and deploy machine learning models that meet business requirements.
  • Develop and maintain continuous integration and delivery pipelines for machine learning models, ensuring that they are tested, validated, and deployed in a consistent and reliable manner.
  • Perform data analysis and feature engineering to support machine learning model development.
  • Stay up to date with the latest advancements in machine learning and MLOps and evaluate new technologies that can improve our processes and models.
  • Provide mentorship and technical guidance to junior data scientists and machine learning engineers.
  • Leveraging open-source tools and building frameworks and components to improve and scale our Serving and ML platform

Requirements

  • Experience in both architecting and the hands-on implementation of infrastructure
  • Must have experience in the Media, Advertising or Marketing Industry
  • Can deploy ML model to a production cloud environment
  • Hands-on experience in GCP, Databricks or Apache Spark mandatory
  • Strong knowledge of ETL concepts and data processing workflows
  • Experience with ML libraries and predictive analytics
  • Experience with Sagemaker AWS, Kafka, Python, R, SQL and NoSQL Databases, Spark, Scikit-Learn, Keras/TensorFlow, PyTorch, Docker, CI/CD Pipelines, Git, or developing APIs.
  • Computer Science Degree or related field
  • 1 or more years of industry experience building scalable services and data driven platforms.
  • Experience with building ML infrastructure, writing production level code, & deploying Machine Learning models
  • Experience working on complex problems and systems where scalability and performance are very important
  • Strong problem solving and debugging skills. Entrepreneurial individuals who are passionate about AI ethics and causality

Required Skills

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