Environmental Data Analyst

• 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.

with embedded and analytical database engines (e.g., SQLite, DuckDB) for local analysis, prototyping, and data interchange.

• 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.

• 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.