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a demonstrated ability to use a statistical programming language such as R or Python. Domain knowledge demonstrated by a degree in economics, data science, statistics, forestry, natural resources
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, coastal hydrodynamics, data handling, preprocessing, and visualization techniques. Proficiency in programming languages such as Python and/or MATLAB. The candidate should also have a strong background in
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Preferred: Familiarity with international energy data sources (e.g., IEA, EIA, OPEC). Familiarity with programming or data tools (e.g., Python, R, SQL, Tableau). Understanding of global energy markets, trends
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large forest resource data using R, Python, and/or GIS software Knowledge of hardwood systems, including management practices, current markets, stand dynamics, environmental change pressures, and