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Data Intern Responsibilities: Conduct advanced R-based modeling for comprehensive data analysis, specifically tailored to a data-driven business in the telecommunications sector. This includes predictive analytics to enhance customer insights and...

Data Intern


Responsibilities:

  • Conduct advanced R-based modeling for comprehensive data analysis, specifically tailored to a data-driven business in the telecommunications sector. This includes predictive analytics to enhance customer insights and network performance.
  • Develop and refine prediction algorithms to improve the efficiency of existing models in managing virtual network operations. This includes optimizing resource allocation and predicting network demand.
  • Experiment with a range of statistical and machine learning models, including but not limited to KNN (K-nearest neighbors), NN (neural networks), and hierarchical models, to address complex problems in data analysis and prediction accuracy.
  • Collaborate closely with IT and Pricing teams to align data science strategies with business objectives. This involves the integration of data science models into business decision-making processes, emphasizing meticulous attention to detail.
  • Lead initiatives to identify and implement improvements in the efficiency and effectiveness of existing predictive models, contributing to the overall optimization of business operations.
  • Analyze large datasets and articulate the results clearly and effectively, utilizing advanced data visualization tools such as Tableau or Power BI to create insightful reports and presentations for stakeholders.
  • Participate in the development and deployment of R-Shiny applications, enabling interactive data exploration and visualization to support decision-making processes.

Requirements:

  • Currently enrolled as a student in Mathematics, Statistics, Applied Statistics, or Data Science, with a strong academic record.
  • Solid foundation in statistics and proficiency in programming with R, including a deep understanding of R's statistical and machine learning packages.
  • Demonstrated experience in using machine learning algorithms for data analysis and model development. This includes practical application of models in real-world scenarios.
  • Strong in Python (and R) , with a focus on optimizing Python functions for data analysis and model development. This includes experience with Python's data science libraries (e.g., pandas, NumPy, scikit-learn).
  • Strong skills in data visualization and reporting, with experience in using tools like Tableau or Power BI to create dynamic reports and dashboards.
  • Strong knowledge of SQL.
  • Interest in financial modeling and experience with developing pricing models to support business objectives. This includes understanding the principles of pricing strategy in the context of the telco sector.
  • ⁠Keen interest in developing frontend applications for data presentation, particularly using R-Shiny, to facilitate interactive data exploration and visualization.
  • Excellent problem-solving skills, with the ability to work independently and in team settings. Strong communication skills are essential for presenting complex data in an understandable manner to non-technical stakeholders.
  • Advanced level of English


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