ICT Analyst – Fullstack AI Engineer

jobs-near-me.org

Job categories IT
Vacancy code VA/2024/B5502/28991
Level ICS-8
Department/office AR, EAPMCO, Indonesia
Duty station Home based
Contract type International ICA
Contract level IICA-1
Duration 6 months with a possibility of extension
Application period 04-Oct-2024 to 18-Oct-2024
Applications to vacancies must be received before midnight Copenhagen time (CET) on the closing date of the announcement.

Functional Responsibilities

Under the general guidance and supervision of the ICT Specialist- Technology Innovation, the incumbent responsibilities include the following:

  1. Implementation of the supporting systems of DISHA’s analytics services 

  2. Support on the implementation of DISHA’s data access and processing platform

  3. Quality Assurance of DISHA’s analytics services.

1. Implementation of the supporting systems of DISHA’s analytics services
  • Implement a mechanism of ML experiment tracker (hyperparameters and data versions) and model deployment.

  • Implement a mechanism of analytics and predictive serving through embedded business intelligence.

  • Support DISHA’s data scientists in model exploration and experimentation. 

  • Support DISHA’s data engineers in building data pipelines that go from-and-to our analytics services, as well as the raw data that fuels the ML training.

 2. Support on the implementation of DISHA’s data access and processing platform

  • Support the platform engineers in implementing the external data access connection and ensure that it seamlessly flows into the data pipeline and into the analytics services

  • Support the platform engineers in informing the scalability requirements of the end-to-end data processing platform.

 3. Quality Assurance of DISHA’s analytics services.

  • Implement a model monitoring system to detect data drift and model performance degradation.

  • Support DISHA’s platform lead to implement health check for our analytics services, such as VMs that run the BI tools and model serving.

  • Support DISHA’s data scientists in maintaining up a clean, non-leaking, and growing data splits for ML model development.

Impact of Results:

The effective and successful achievement of Disha objectives could accelerate the ability of social and humanitarian actors to utilize the benefits of AI and big data at a faster pace in these unprecedented times of fragility and uncertainty of climate-fuelled natural disasters and intense conflicts.

Education/Experience/Language requirements

Education:
  • First-level university degree (Bachelor’s or equivalent) in computer science or a related field is required.

  • An advanced University Degree (Master’s or equivalent) or higher degree in computer science or a related field is an advantage.

Experience:

  • A minimum of two (2) years of experience in engineering of data-intensive applications, in machine learning, or in data science is required.
  • Experience in designing and deploying data-driven applications in the cloud including data processing, predictive analysis, and reporting/visualization is required.
  • Experience in programming with Python is desirable.
  • Experience in deploying and using BI tools is preferred. Experience in making customized views on top the BI tools (e.g. using javascript libraries) is desirable.
  • Experience in programming with one or more of currently popular ML/AI frameworks such as TensorFlow, PyTorch, etc. is desirable.
  • Familiarity with MLOps best practices is desirable. 
  • Familiarity with the product offering of Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure as used to implement data ingestion, processing, and model deployment architectures is an asset;
  • Excellent communication skills are desirable with the ability to explain complex analytical concepts to people from other backgrounds and disciplines;
  • Experience working with the UN system is an asset.
Language Requirements:
  • Full working knowledge of English is required;
  • Knowledge of another official UNOPS language is an asset

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