Hardship Level (not applicable for home-based)A (least hardship)
Family Type (not applicable for home-based)
Family
Staff Member / Affiliate TypeInternship
Target Start Date2024-05-01
Job Posting End DateApril 29, 2024
Terms of ReferenceTerm of References for Data Science Intern
Position: Data Science Intern
Unit: Data Analysis Group (DAG), UNHCR Jordan
Duration: [Six Month]
Location: [DAG Amman]
Reporting to: [Shahzad ASGHAR asghar@unhcr.org]
Background
The Data Analysis Group (DAG) at UNHCR Jordan is committed to harnessing the power of artificial intelligence and data science to enhance our humanitarian efforts. Our projects focus on predictive analytics and time series analysis to aid decision-making processes. The intern will play a pivotal role in advancing our current projects by applying sophisticated data analysis techniques and developing new methods to interpret complex datasets.
Objective
To support DAG's ongoing AI and data projects through the application of advanced SQL, Python, and other statistical computer languages, contributing to the development and execution of machine learning models and data analytics solutions.
Duties and Responsibilities
• Assist in the design and implementation of models for predictive and time series analysis.
• Write and optimize advanced SQL queries and Python scripts for data analysis tasks.
• Apply machine learning techniques such as clustering, decision tree learning, and neural networks to UNHCR’s ProGres and RAIS datasets.
• Conduct statistical analysis using regression, random forests, boosting techniques, and other advanced statistical methods.
• Participate in data mining activities including text mining, social network analysis, and other forms of data interpretation.
• Engage in the visualization of data sets using Python, R, or various BI tools to create insightful representations of data trends and patterns.
• Collaborate with team members to refine data-driven strategies and improve existing analytical processes.
Qualifications
• Knowledge of data analytics and machine learning.
• Proficient in statistical computer languages such as R, Python, and SQL.
• Understanding of a variety of machine learning techniques and their real-world implications.
• Knowledge of advanced statistical techniques and their applications.
• Experienced in querying databases and performing complex data analysis.
• Familiarity with descriptive, predictive, and prescriptive analytics.
• Capable of creating and implementing advanced machine learning algorithms and statistics: regression, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Strong analytical and problem-solving skills.
• Ability to work in a multicultural team and adapt to diverse environments.
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Other informationThis position doesn't require a functional clearance
Home-BasedNo