Forestry Data Science Intern: Planning&Biometrics (Remote)

American Forest Management; Charlotte (NC); On-site; USD 25,000 - 30,000; Full time

Benefits offered by this job

Scholarship program

Remote work option

Hands-on forestry projects

Job summary

American Forest Management invites a motivated Resource Planning and Biometrics Intern to join the RPBS group in Charlotte, NC. The role focuses on applying R and Python to analyze forest data, manage large datasets in Postgres/SQL, and develop predictive forest models.

You will collaborate with biometricists and forest planners, integrating geospatial data and building tools to improve inventory and growth projections. Remote work is possible, with a scholarship opportunity for top performers.

Qualifications

• Bachelor’s degree in forestry, geospatial sciences, or related field.
• Working toward a master's degree preferred, ideally in biometrics or quantitative forestry.
• Experience with forest systems (metrics and silviculture) at a bachelor’s level or higher.
• Strong programming skills in R and/or Python (bonus: Jupyter Notebooks, or R Shiny).
• Solid understanding of statistics and quantitative methods. Ability to manage large, messy datasets.
• Familiarity with GIS software (QGIS, ESRI), forest growth and yield models (FVS), or linear programming software (Woodstock).
• Strong problem-solving skills and creativity.
• Growth mindset and team collaboration.
• Professional integrity, independent and team work.

Responsibilities

• Apply advanced analytical tools such as R and Python to manipulate, analyze, and visualize complex forest and remotely sensed data.
• Work with standard data structures and formats (Postgres, SQL, Excel) to clean, organize, and process large datasets.
• Develop and test forest growth models, predictive analytics, and decision-support tools to enhance forest management strategies.
• Automate complex processes using R, Python, and other relevant platforms.
• Integrate geospatial data (e.g., Sentinel-2, LiDAR) into forest planning and/or forest growth models.
• Collaborate with experienced biometricians and forest planners to address complex forest management challenges.
• Build creative and effective solutions that drive better decisions in forest inventory, silviculture, harvesting, and growth modeling.
• Share insights and tools with the team to build collective capacity.

Skills

R programming

Python programming

GIS

Statistical analysis

Data visualization

Big data

Education

Bachelor’s degree in forestry or geospatial sciences

Master's degree preferred

Tools

Postgres

SQL

Excel

QGIS

ESRI

FVS

Woodstock

Job description

American Forest Management invites a motivated Resource Planning and Biometrics Intern to join the RPBS group in Charlotte, NC. The role focuses on applying R and Python to analyze forest data, manage large datasets in Postgres/SQL, and develop predictive forest models.

You will collaborate with biometricists and forest planners, integrating geospatial data and building tools to improve inventory and growth projections. Remote work is possible, with a scholarship opportunity for top performers.