Assistant Data Scientist

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Description

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• Collaborate with the team on the development of the data science methodology to support deduplication within UNHCR registration data, with responsibilities including:
• Data familiarization: Gain a deep understanding of the UNHCR registration data structure and data entities as well as deduplication policy and processes as applied on a daily basis in UNHCR operations.
• Database understanding: Analyze data entities, relationships, and data quality issues within registration data.
• Identifying and developing suitable models: Utilize machine learning algorithms to implement deduplication, integrating data from the registration data.
• Collaboration and communication: Continuously collaborate with relevant teams within the organization on registration data to gather requirements and ensure alignment.
• Identify and pre-process data: Utilize data cleansing and transformation techniques to prepare data from registration data.
• Model development and optimization: Training and testing machine learning models for the detection of duplicate case entries within the registration data, incorporating data from proGres.
• Documentation: Ensure thorough documentation of all processes, including model selection, data preprocessing steps, and model performance, as well as the integration of registration data.
• Support for Fraud Detection Tools
• Collaborate with the registration team to support the development of ML/AI-enhanced fraud detection tools, focusing on operator-driven manipulations and fraud.
• Conceptualize a scalable set of analysis products, which can be deployed to all 130+ country operations using the system.

• Understand the complexities of the resettlement process, selection criteria and the nuances of UNHCR’s proGres data that inform the process.
• Draw on good practices in operations, having developed a data-driven resettlement selection process.
• Identify relevant data entities within proGres and recognize challenges and caveats in resettlement data.
• Support with the development, testing, and evaluation of predictive models capable of assessing the probability of individual resettlement based on historical proGres data and selected features.
• Documentation: Ensure comprehensive documentation of the entire process within Microsoft Power Platform, including key steps and limitations of AI models and the use of proGres data. 

• Support the development and deployment of a deduplication tool for identifying duplicates in UNHCR’s registration database.
• Support the development of a predictive model based on registration data to assess statistical probabilities for the purpose of expediting resettlement identification. 
• Support the development of fraud detection algorithms based on registration data, specifically log data.
• Communicate with other internal teams to develop collaborative frameworks and to harmonize ways of working together.

• University Degree in statistics, data science, mathematics, economics, or other quantitative social sciences.

• 1 year of relevant experience with Undergraduate degree; or no experience with Graduate degree; or no experience with Doctorate degree
• Demonstrated experience in data collection, management, cleaning, processing, and applied data analysis.
• Demonstrated experience user of the statistical programming languages R and/or Python.
• Demonstrated experience with using SQL.
• Demonstrated experience working with alternative data sources and/or statistical learning methods.
• Demonstrated experience in ensuring the operational relevance of analytical and/or research work.
• Demonstrated experience writing technical reports.
• Demonstrated experience presenting work to both technical and non-technical audiences. 

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