2027 Resource Planning and Biometrics Intern

AMERICAN FOREST MANAGEMENT INC
Charlotte, North Carolina, United StatesPosted Sep 4, 2026
Year-round

About the role

Job DetailsJob Location: Charlotte, NC 28217Position Type: InternshipSalary Range: $18.00 - $22.00 Hourly American Forest Management (AFM) is seeking a motivated and curious Resource Planning and Biometrics Intern to join the Resource Planning and Biometric Services (RPBS) group at AFM. RPBS is responsible for providing forest planning services which support client land management and forest investment decisions, as well as biometric services necessary for planning projections, inventory analysis, and data systems. This position will be based at our Headquarters in Charlotte, NC or can be remote based and offers a unique opportunity to apply cutting-edge data science methods to real-world forestry challenges. If you’re excited about working with big data, collaborating with some of the largest forestland holders in the country and producing deliverables that matter please consider applying. As part of our 2027 Internship Program, interns will also have the exciting opportunity to compete for a $2,500 scholarship. This scholarship will be awarded to an intern who demonstrates outstanding performance, initiative, and alignment with our company values throughout the program. It’s our way of recognizing and rewarding the hard work, creativity, and dedication of our interns while investing in their continued growth and success. Primary Duties and 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, etc.) 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 pla

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