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Artificial Intelligence And Machine Learning Expert

Closing: May 24, 2024

This position has expired

Published: May 13, 2024 (16 days ago)

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Job Summary

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  • SoCha is developing an AI Analysis Model and will be leveraging AI modeling techniques to analyze data from an upcoming assessment of community perception on Preventing Conflict and Violent Extremism (PCVE) efforts in selected counties in Kenya. The aim of the AI Analysis Model is to uncover hidden patterns, trends, and correlations that traditional analytical methods may overlook. This AI analysis is expected to provide a more nuanced understanding of community dynamics and perceptions on PCVE. SoCha is therefore seeking an Artificial Intelligence and Machine Learning Expert to create this AI Analysis Model.

Minimum Qualifications and Expertise

  • Bachelor’s degree in Data Science, Computer Science, Statistics or a related field.
  • At least five (5) years of experience in data science, with specific expertise in AI and machine learning. Experience in handling natural language datasets is essential.
  • Proficiency in statistical analysis. Experience in integrating qualitative insights with quantitative data to provide comprehensive analysis.
  • Proficiency in Python or R programming languages.
  • Extensive experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Strong background in statistical modeling and data mining techniques.
  • Ability to interpret complex data and turn it into actionable insights. Strong problem-solving skills and attention to detail.
  • Understanding of PCVE (Preventing/Countering Violent Extremism) programs and related social issues is highly desirable.
  • Published research or projects in relevant areas of AI, social science, or community studies would be an advantage.


Responsibilities
  • SoCha is developing an AI Analysis Model and will be leveraging AI modeling techniques to analyze data from an upcoming assessment of community perception on Preventing Conflict and Violent Extremism (PCVE) efforts in selected counties in Kenya. The aim of the AI Analysis Model is to uncover hidden patterns, trends, and correlations that traditional analytical methods may overlook. This AI analysis is expected to provide a more nuanced understanding of community dynamics and perceptions on PCVE. SoCha is therefore seeking an Artificial Intelligence and Machine Learning Expert to create this AI Analysis Model.

Minimum Qualifications and Expertise

  • Bachelor’s degree in Data Science, Computer Science, Statistics or a related field.
  • At least five (5) years of experience in data science, with specific expertise in AI and machine learning. Experience in handling natural language datasets is essential.
  • Proficiency in statistical analysis. Experience in integrating qualitative insights with quantitative data to provide comprehensive analysis.
  • Proficiency in Python or R programming languages.
  • Extensive experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Strong background in statistical modeling and data mining techniques.
  • Ability to interpret complex data and turn it into actionable insights. Strong problem-solving skills and attention to detail.
  • Understanding of PCVE (Preventing/Countering Violent Extremism) programs and related social issues is highly desirable.
  • Published research or projects in relevant areas of AI, social science, or community studies would be an advantage.


In collaboration with the Evaluations Manager and the IT team, the selected candidate will:

  • Develop tailored AI prompts for qualitative data analysis using the most appropriate large language models (LLMs).
  • Build a model-agnostic data pipeline in Python, including API calls, data preprocessing, and output handling.
  • Establish metrics to assess model performance and conduct initial tests with a subset of data.
  • Apply advanced AI modeling techniques to analyze data, identifying and interpreting trends, patterns, and correlations in community perceptions.
  • Incorporate feedback to refine the model, enhancing both the accuracy and relevance of the outputs.
  • Conduct descriptive and correlational statistical analyses to further illuminate community perspectives on PCVE efforts.
  • Work with subject matter experts to review model outputs, validate their accuracy and applicability, and make iterative improvements based on expert feedback.
  • Document and present findings in visually compelling formats, ensuring that reports and presentations effectively communicate key insights to stakeholders, facilitating informed decision-making regarding PCVE strategies and interventions.


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