Analyse Environment-related Data Using Python

Contract

This is a UNV contract. More about UNV contracts.

Our objective is to empower policymakers, researchers, and stakeholders by providing them with in-depth analysis and clear visualisations that can guide environmental decision-making towards sustainability and conservation goals. The insights gained from this analysis will be crucial in addressing complex environmental issues such as climate change, biodiversity loss, and ecosystem degradation.

To that end, we are seeking to collaborate with Online Volunteers in this project where online volunteers will play a key role in transforming raw data into actionable intelligence, enabling the MDF and its partners to track environmental changes, assess the effectiveness of interventions, and plan future strategies.

We are seeking the support of four (4) online volunteers to undertake a comprehensive analysis of environment-related data using Python. Each online volunteer will have a distinct task as follows:

Data Collection: This online volunteer will focus on identifying and gathering relevant environmental datasets from multiple sources. They will ensure the data is accurate, reliable, and structured for effective analysis.

Data Processing: Responsible for cleaning and pre-processing the data, this online volunteer will write Python scripts to handle missing data, normalise data, and perform other preprocessing steps to prepare the datasets for analysis.

Data Analysis: This online volunteer will support in developing Python code to conduct statistical analysis and apply data science techniques. Their role is to uncover patterns, trends, and correlations within the data that can inform environmental strategies.

Data Visualisation: The online volunteer will use Python libraries such as Matplotlib, Seaborn, or other visualisation tools to create intuitive graphics and dashboards. These visualisations will communicate the findings to both technical and non-technical stakeholders.

Collaboration and effective communication among the online volunteers will be essential to ensuring that the data is accurately interpreted and the results are actionable. Online Volunteers will regularly meet online to discuss progress, challenges, and insights.

1. Demonstrated proficiency in Python, with experience in data manipulation and analysis libraries such as Pandas, NumPy, and others.
2. Strong background in data analysis, statistical modelling, machine learning, and/or data visualisation.
3. Familiarity with environmental science and sustainable development, and the ability to interpret and analyze relevant datasets.
4. Adept at problem-solving and analytical thinking with a capacity to work both independently and as part of a remote team.
5. A minimum of a bachelor's degree in computer science, data science, environmental science, or a related discipline, with relevant experience in data analysis.
6. Excellent communication skills in English, with the ability to articulate findings to a diverse audience; additional UN language proficiency is beneficial.