Data Science

Location:

• 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.
  

Details

Originally posted on Himalayas