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Data Science

Role overview

Qualifications

  • Bachelor's degree in Business Administration (Big Data Analytics), Economics, Statistics, or a related field.
  • 3-5 years of experience in data science, with a strong focus on predictive analytics and machine learning.
  • Proficiency in Python, SQL, SAS, and advanced Excel.
  • Experience with BI tools like Power BI and Tableau; strong understanding of psychometric models and advanced statistical methods; familiarity with Graph API and OData endpoints; experience with large language models (LLMs), retrieval-augmented generation (RAG), and vector databases.

Responsibilities

  • Develop and implement data science models to enhance learning, assessment, and training platforms.
  • Conduct data analysis, statistical analysis, and predictive modeling to identify trends and patterns in educational data; apply ML models (logistic regression, random forest, clustering) and psychometric methods (Item Response Theory and Rasch Models) to improve assessments.
  • Create data visualizations and dashboards using Power BI and Tableau for educational stakeholders; collaborate with educators and researchers to understand requirements and deliver insights; optimize ETL processes for educational datasets.
  • Support adaptive learning systems and personalized learning experiences through data-driven approaches; implement and utilize Graph API and OData endpoints to integrate and analyze data from various sources; work with large language models (LLMs) and retrieval-augmented generation (RAG) techniques to enhance educational tools; leverage vector databases to store and retrieve high-dimensional data.

About the company

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GamaLearn

Company details

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Job description

This is a remote position.

  • Develop and implement data science models to enhance learning, assessment, and training platforms.
  • Conduct data analysis, statistical analysis, and predictive modeling to identify trends and patterns in educational data.
  • Develop machine learning models including logistic regression, random forest, and clustering algorithms tailored for educational purposes.
  • Use psychometric methods like Item Response Theory and Rasch Models to improve assessment data quality.
  • Create data visualizations and dashboards using Power BI and Tableau for educational stakeholders.
  • Work with cross-functional teams, including educators and researchers, to understand requirements and deliver insights.
  • Optimize ETL processes for data integration and preprocessing specific to educational datasets.
  • Support the development of adaptive learning systems and personalized learning experiences through data-driven approaches.
  • Implement and utilize Graph API and OData endpoints to integrate and analyze data from various sources.
  • Work with large language models (LLMs) and retrieval-augmented generation (RAG) techniques to enhance educational tools and provide personalized learning experiences.
  • Leverage vector databases to store and retrieve high-dimensional data efficiently.


Requirements



  • Bachelor's degree in Business Administration (Big Data Analytics), Economics, Statistics, or a related field.
  • 3-5 years of experience in data science, with a strong focus on predictive analytics and machine learning.
  • Proficiency in Python, SQL, SAS, and advanced Excel.
  • Experience with BI tools like Power BI and Tableau.
  • Strong understanding of psychometric models and advanced statistical methods.
  • Proven experience in implementing Graph API and working with OData endpoints.
  • Experience with large language models (LLMs), retrieval-augmented generation (RAG), and vector databases.
  • Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.
  • Proven track record of improving educational outcomes through data-driven strategies.
  • Strong background in statistical analysis, including exploratory data analysis and inferential statistics.

Preferences:

  • Certification in Power BI or similar BI tools.
  • Experience in educational data analysis and resource allocation optimization.
  • Knowledge of NLP techniques and sentiment analysis is a plus.
  • Strong analytical skills and attention to detail.
  • Ability to work in a collaborative team environment and manage multiple projects simultaneously.


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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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