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Remote Chemistry Data Science information

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$37.5K

$122.7K

$196.5K

How much do remote chemistry data science jobs pay per year?

As of Aug 3, 2026, the average yearly pay for remote chemistry data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a remote chemistry data scientist?

A Remote Chemistry Data Scientist is a professional who uses data science techniques to analyze and interpret chemical data, all while working remotely. They apply statistical modeling, machine learning, and computational methods to solve problems in chemistry, such as predicting chemical properties or optimizing experiments. These professionals often collaborate with chemists, researchers, and engineers to extract actionable insights from large datasets. Working remotely allows them to perform these tasks from anywhere, using digital communication and collaboration tools.

What is the difference between Remote Chemistry Data Science vs Remote Chemical Engineering Data Science?

AspectRemote Chemistry Data ScienceRemote Chemical Engineering Data Science
Required CredentialsBachelor's or Master's in Chemistry, Data Science skillsBachelor's or Master's in Chemical Engineering, Data Science skills
Work EnvironmentResearch labs, pharmaceutical companies, biotech firmsManufacturing plants, process industries, chemical companies
Employer & Industry UsageResearch & development, product formulation, quality controlProcess optimization, safety analysis, plant operations
Common Search & Comparison IntentUnderstanding roles in chemistry-focused data science jobsExploring data science roles in chemical engineering contexts

Remote Chemistry Data Science focuses on applying data analysis to chemical research, product development, and quality control within chemistry-related industries. In contrast, Remote Chemical Engineering Data Science emphasizes process optimization and plant operations in chemical manufacturing. While both roles require data science skills and chemistry or engineering backgrounds, their work environments and industry applications differ significantly.

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

To thrive as a Remote Chemistry Data Scientist, you need a strong background in chemistry, data analysis, and statistical modeling, often supported by an advanced degree in chemistry, data science, or related fields. Familiarity with programming languages like Python or R, cheminformatics tools, and data visualization platforms is typically required. Excellent problem-solving, communication, and self-motivation skills help you manage remote work, collaborate with interdisciplinary teams, and explain complex findings clearly. These capabilities are crucial for deriving actionable insights from chemical data and driving innovation in research and industry from a remote setting.

How do remote chemistry data scientists typically collaborate with laboratory teams and other stakeholders?

Remote Chemistry Data Science professionals often collaborate with laboratory teams and other stakeholders through virtual meetings, cloud-based data sharing platforms, and project management tools. Effective communication is key, as they translate complex data analyses into actionable insights for researchers and management. Regular check-ins, collaborative documentation, and participation in virtual lab discussions help ensure alignment on project goals and timelines. Building strong relationships remotely can be a challenge, but leveraging digital collaboration tools and proactive communication helps maintain productivity and teamwork.
More about Remote Chemistry Data Science jobs
What cities are hiring for Remote Chemistry Data Science jobs? Cities with the most Remote Chemistry Data Science job openings:
What are the most commonly searched types of Chemistry Data Science jobs? The most popular types of Chemistry Data Science jobs are:
What states have the most Remote Chemistry Data Science jobs? States with the most job openings for Remote Chemistry Data Science jobs include:
What job categories do people searching Remote Chemistry Data Science jobs look for? The top searched job categories for Remote Chemistry Data Science jobs are:
Remote Chemistry Data Science jobs near you
Infographic showing various Remote Chemistry Data Science job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Environmental Data Analyst

GSI Environmental Inc.

Olympia, WA • On-site, Remote

$76K - $110K/yr

Full-time

Posted 27 days ago

Job description

Description

GSI is seeking an Environmental Data Analyst who combines technical ability, analytical creativity, and business acumen to strengthen our data management, analysis, and visualization team. The ideal candidate is comfortable across the full data lifecycle—building and maintaining relational databases, developing analysis and automation pipelines in SQL, Python, and/or R, and providing query, reporting, and visualization support in a collaborative organization working closely with technical staff. Familiarity with environmental chemistry data generated from field investigations of water, soil, sediment, air, and biological matrices is valued. The candidate should know how to analyze system requirements and be familiar with relational databases, statistical analysis, and modern data visualization techniques using relevant and current tools.

GSI provides high-quality technical and regulatory expertise to industry and government to address a broad range of environmental issues. We specialize in solving complex environmental problems by leveraging our extensive knowledge of environmental regulations, stressing accurate data collection and analysis, and applying new technologies to our clients' most difficult challenges.

Responsibilities

  • Support environmental investigation projects by maintaining relational databases of environmental chemistry data from historical reports, laboratory test results, web sources, and third-party databases.
  • Build and maintain ETL (extract, transform, load) and analysis workflows in SQL, Python, and/or R to clean, transform, validate, and analyze environmental datasets.
  • Work with multi-disciplinary teams of engineers and scientists to support statistical and spatial analyses.
  • Build dashboards and visualizations, and format tables, charts, and graphs to style guidelines for technical reports and presentations.
  • Organize data in structures that support automation and downstream analysis.
  • Perform quality assurance on analytical databases to ensure data integrity, and identify and correct data gaps, errors, and relational table issues.
  • Support a wide variety of projects ranging from litigation support and site investigation to data mining for research and development.
  • Effectively communicate findings to internal and external clients.
  • Complete assigned tasks on schedule and within budget while meeting quality standards on deliverables.
  • BS/BA or higher degree in data science, computer science, statistics, environmental science, or a related field.
  • 2-5 years of work experience in data management or analysis, with strong relational database skills using PostgreSQL, Microsoft SQL Server, Microsoft Access, or other database management systems.
  • Comfortable writing advanced SQL for data management (beyond basic create, read, update, delete), to clean, transform, and structure data in relational databases.
  • Familiarity with relational database design, data modeling, and normalization.
  • Awareness of data compilation, migration, and backup/retention considerations.
  • Shell scripting (Bash) and comfort working in Linux and command-line environments.
  • Experience using Python and/or R (Tidyverse, Shiny) for data analysis, visualization, dashboards, and web applications, including hands-on project work.
  • Self-motivated and eager to learn, with a drive to adopt new data and analysis techniques, AI, and emerging technologies to improve workflows.
  • Excellent written and verbal communication, and the ability to manage multiple tasks and meet deadlines with limited supervision.
  • Strong problem-solving skills and attention to detail.
  • Additional preferred skillsets and qualifications include:
    • Familiarity with chemistry data, laboratory information management systems (LIMS), data validation, and extraction of data from online sources.
    • Version control (Git) and reproducible, scripted analysis workflows.
    • Application development and deployment, including web frameworks for data tools (e.g., Django, Flask/FastAPI, Dash, Streamlit, R Shiny). Familiarity with containerization (Docker) is a plus.
    • Experience with embedded and analytical database engines (e.g., SQLite, DuckDB) for local analysis, prototyping, and data interchange.

Job Perks

  • Competitive salary and benefits
  • Quarterly and year-end bonuses
  • Flexible work environment with potential for remote work
  • On-the-job training, mentorship, and professional development
  • Participation in conferences, technical presentations, and papers
  • Collaborative atmosphere
  • Base salary will vary depending on qualifications and experience.

The anticipated salary range for this position is $76,000–$110,000. This range represents GSI's good-faith estimate of the base salary for the position and is provided in accordance with applicable pay transparency laws. Starting salary will be determined based on several job-related factors, including relevant experience, education, professional licensure, certifications, technical expertise, geographic location, internal equity, and overall qualifications.

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