Environmental Data Scientist - Hybrid (Ecology & Restoration)

IEc; Cambridge (MA); Hybrid; USD 70,000 - 90,000; Full time

Benefits offered by this job

Health Savings Account

Retirement contributions

Professional development opportunities

Job summary

Industrial Economics, Incorporated (IEc) seeks a Scientist to support natural resource damage assessment, oil spill assessment, environmental impact analyses, remedial investigations, applied natural resource management and restoration planning in Cambridge, MA. The role emphasizes data-driven analyses, GIS, and remediation planning across site-specific projects with hybrid work options.

The position requires a Master’s or PhD in a relevant field, strong data scripting skills (Python/R), and the

Qualifications

• Master's degree or PhD in ecology, biology, toxicology, geology, chemistry, hydrogeology, hydrology, or similar field.
• Experience with data analysis in a scripting or database environment (Python, R).
• At least one quantitative skill such as GIS, geostatistics, relational database design, or other proficiency related to science.

Responsibilities

• Gather, manage, and evaluate large environmental datasets.
• Design and implement quantitative analyses using scientific methods.
• Synthesize information, conduct GIS analyses, apply statistics, interpret and communicate results.
• Draft technical deliverables and review documents.

Skills

Data analysis

Quantitative skills

Education

Master's or PhD in ecology/biology/toxology/geology/chemistry/hydrogeology/hydrology

Tools

Python

R

SQL

ArcGIS Pro

Job description

Industrial Economics, Incorporated (IEc) seeks a Scientist to support natural resource damage assessment, oil spill assessment, environmental impact analyses, remedial investigations, applied natural resource management and restoration planning in Cambridge, MA. The role emphasizes data-driven analyses, GIS, and remediation planning across site-specific projects with hybrid work options.

The position requires a Master’s or PhD in a relevant field, strong data scripting skills (Python/R), and the