Data Science

Category: Technology

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