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Environmental Data Science Jobs in Pennsylvania (NOW HIRING)

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Work Environment The firm's work location requirements may be modified at the firm's discretion.

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Environmental Data Science information

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$37.6K

$123K

$197K

How much do environmental data science jobs pay per year?

As of Sep 8, 2026, the average yearly pay for environmental data science in Pennsylvania is $123,033.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $136,300.00 per year, depending on experience, location, and employer.

What is environmental data science?

Environmental Data Science is an interdisciplinary field that uses statistical, computational, and analytical techniques to collect, analyze, and interpret large sets of data related to the environment. Professionals in this field work on issues like climate change, pollution, biodiversity, and natural resource management by extracting meaningful insights from complex environmental datasets. Their work supports decision-making for policy, conservation, and sustainability initiatives. Environmental data scientists often collaborate with ecologists, geographers, and policymakers to address environmental challenges using data-driven approaches.

What are some common challenges faced by environmental data scientists when working with real-world datasets?

Environmental data scientists often encounter challenges such as incomplete or inconsistent data, varying data formats, and the need to integrate information from multiple sources like sensors, satellites, and field observations. Addressing missing values, data quality issues, and ensuring proper geospatial alignment can be time-consuming but is essential for producing reliable analyses. Collaboration with domain experts and stakeholders is frequently required to interpret findings and ensure that the results are actionable for environmental policy or management decisions.

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

To thrive as an Environmental Data Scientist, you need strong quantitative skills, expertise in environmental science, and a relevant degree in data science, statistics, or a related field. Familiarity with data analysis tools such as Python, R, GIS software, and experience with large datasets or machine learning techniques is typical. Exceptional problem-solving abilities, communication skills, and attention to detail set top performers apart in this field. These competencies are crucial for effectively interpreting complex environmental data, informing policy, and driving impactful sustainability initiatives.

What is the difference between Environmental Data Science vs Environmental Data Analyst?

AspectEnvironmental Data ScienceEnvironmental Data Analyst
Required CredentialsTypically requires a degree in data science, environmental science, or related fields; often includes programming and statistical certificationsUsually requires a degree in environmental science, geography, or related fields; may include basic data analysis certifications
Work EnvironmentResearch labs, data centers, environmental agencies, or consulting firmsEnvironmental agencies, research organizations, or consulting firms
Employer & Industry UsageUsed in environmental research, climate modeling, and policy analysisUsed in environmental monitoring, reporting, and data interpretation

Environmental Data Science focuses on developing models and algorithms to analyze complex environmental data, often requiring advanced programming skills. In contrast, Environmental Data Analysts primarily interpret and visualize environmental data to support decision-making. Both roles are vital but differ in technical depth and scope.

Is environmental data science a good major?

Environmental Data Science is a relevant major for careers involving analyzing environmental data, modeling ecological systems, and supporting sustainability efforts. It typically combines skills in data analysis, programming, and environmental science, preparing graduates for roles in research, consulting, or government agencies.

What does an environmental data scientist do?

An environmental data scientist analyzes environmental data to identify patterns, assess environmental risks, and support decision-making. They use statistical tools, programming languages like Python or R, and GIS software to interpret large datasets related to climate, pollution, and natural resources.
Infographic showing various Environmental Data Science job openings in Pennsylvania as of August 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $123,033 per year, or $59.2 per hour.

Full-time

Re-posted 8 days ago


Children's Hospital Of Philadelphia rating

8.4

Company rating: 8.4 out of 10

Based on 96 frontline employees who took The Breakroom Quiz

71st of 1,065 rated hospitals


Job description

SHIFT:

Day (United States of America)

Seeking Breakthrough Makers
Children’s Hospital of Philadelphia (CHOP) offers countless ways to change lives. Our diverse community of more than 20,000 Breakthrough Makers will inspire you to pursue passions, develop expertise, and drive innovation.
At CHOP, your experience is valued; your voice is heard; and your contributions make a difference for patients and families. Join us as we build on our promise to advance pediatric care—and your career.
CHOP’s Commitment to Diversity, Equity, and Inclusion
CHOP is committed to building an inclusive culture where employees feel a sense of belonging, connection, and community within their workplace. We are a team dedicated to fostering an environment that allows for all to be their authentic selves. We are focused on attracting, cultivating, and retaining diverse talent who can help us deliver on our mission to be a world leader in the advancement of healthcare for children.
We strongly encourage all candidates of diverse backgrounds and lived experiences to apply.
A Brief Overview

The mission of the Campbell Laboratory at the Children’s Hospital of Philadelphia is to ensure that every child with a rare genetic disease is diagnosed as quickly and accurately as possible. We believe that a promising approach is to use large language models (LLMs) to better understand our patients’ health and intervene in the electronic health record to facilitate diagnosis. We hope these approaches can help address inequities in the way genetic care is provided to patients from historically marginalized backgrounds. Our lab performs training of LLMs using both on-premises GPUs as well as by taking advantage of cloud-based resources. We are seeking a data scientist to assist with the collection, standardization, and analysis of data from the electronic health record and to assist in implementation of LLM training in the cloud. The data scientist will have the opportunity to work with physicians, nurses, and laboratory professionals to improve the care of children.

The data scientist will work closely in-person with the laboratory director, Dr. Ian Campbell, and other data scientists and trainees to advance the mission of the laboratory. The laboratory’s LLMs are implemented in Python (PyTorch, JAX) using data extracted from electronic health record (Epic) relational databases. Thus, familiarity with Python and basic SQL are required. The data scientist will contribute to reproducible research by committing high quality and well documented code to the enterprise and public GitHub.

The Campbell Lab is committed to diversity and strives to create an equitable work environment for everyone. Individuals from historically marginalized backgrounds are strongly encouraged to apply.


What you will do

  • Perform exploratory data analysis in pediatric biomedical research using machine learning, statistics, and mathematical analysis incorporating heterogeneous and complex data types under direct supervision.
  • Contribute to assessing and implementing computational, algorithmic, and predictive analytic approaches to address biomedical research questions.
  • With guidance, contribute to the experimental design, execution, testing and critical evaluation of methods as applied to translational data science research projects.
  • Contribute to design and implementation of continuous validation plans for production systems that incorporate models and algorithms, providing guidelines and support for large-scale implementation.
  • Implement computational algorithms and experiments for test and evaluation; interprets data to assesses algorithm performance.
  • Participate in communication of research methods, implementation, and results to varied audience of clinicians, scientists, analysts, and programmers.
  • Work closely with hospital operations and electronic health record vendor teams to translate models and algorithms into production applications.
  • Contribute to manuscript writing for results publication, authors abstracts, and present at professional conferences.

Education Qualifications

  • Bachelor's Degree Required
  • Bachelor's Degree Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field Preferred
  • Masters or PhD in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field Preferred

Experience Qualifications

  • At least three (3) years experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects. Required
  • At least four (4) years with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects Preferred
  • At least one year of experience with complex data science, applied statistics, machine learning, or mathematical modeling projects Preferred
  • Natural language processing experience, particularly in the biological and medical domains Preferred
  • Experience with transformer architecture and associated software (e.g., PyTorch, Tensorflow, JAX) is Preferred
  • Experience using distributed computing technologies Preferred
  • Experience with cloud virtual machine environments Preferred

Skills and Abilities

  • Experience and demonstrated ability acquiring new technical/analytic skills and domain knowledge to support successful contribution to research and development projects is required.
  • Experience formulating or contributing to the formulation of analysis plans and selection of appropriate methods.
  • Experience using existing machine learning and analytic tools in either applied educational or professional projects is required.
  • Experience writing code in either applied educational or professional projects using Python is required.
  • Familiarity with relational databases (e.g. Postgres, MySQL) strongly preferred.
  • Strong verbal and written communications skills with the demonstrated ability to explain complex technical concepts to a lay audience.
  • Applied statistics or mathematical modeling experience preferred.
  • Natural language processing experience particularly in the biological and medical domains preferred.
  • Experience using distributed computing technologies (e.g. Akka, MapReduce, Cuda) preferred.
  • Familiarity with graph, key value, and document data stores (e.g. Neo4j, Hadoop, MongoDB) preferred.
  • Experience creating informative visualizations for complex, high dimensional data preferred.


To carry out its mission, CHOP is committed to supporting the health of our patients, families, workforce, and global community. As a condition of employment, CHOP employees who work in patient care buildings or who have patient facing responsibilities must be fully vaccinated against COVID-19 and receive an annual influenza vaccine. Learn more.
Employees may request exemptions for valid religious and medical reasons. Start dates may be delayed until candidates are immunized or exemption requests are reviewed.
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About Children's Hospital of Philadelphia

Sourced by ZipRecruiter

The Children's Hospital of Philadelphia (CHOP) is a renowned healthcare institution dedicated to the welfare of children. Established in 1855 and situated in the heart of Philadelphia, PA, US, it's known primarily for pediatric healthcare services, pioneering new treatments, and conducting notable research in child-related medical disciplines. As an industry trailblazer, CHOP has a well-established reputation in the pediatric healthcare sector and is recognized globally for its innovative approach towards advancing children's healthcare.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Philadelphia, PA, US

Year founded

1855