Job Purpose

• The Data Science Intern will support the Data Science & Analytics team, a Centre of Excellence (CoE) responsible for developing AI/ML solutions and advanced analytics across EDOTCO. The intern will be involved in data preparation, analysis, visualisation, and automation tasks under the guidance of a Specialist, Data Science. This role provides a hands-on learning experience in solving real-world problems in areas such as operations, engineering, and finance.

Key Responsibilities:

• Assist in data wrangling, cleaning, and exploratory analysis using tools like Python and SQL.
• Support dashboard development using Power BI or Tableau.
• Contribute to workflow automation and assist in simple ETL (Extract, Transform, Load) pipeline setups.
• Participate in AI/ML proof of concept (POC) projects such as Generative AI and OCR (Optical Character Recognition).
• Document findings and share insights in a clear and structured format.
• Learn and apply basic concepts in predictive and prescriptive analytics.
• Work closely with the Data Science team to understand how data supports strategic business decisions.

Learning Outcomes:

• Exposure to industry applications of data science in the telecom infrastructure space.
• Experience working with real business data and solving practical problems.
• Mentorship from experienced data scientists on model development, data pipelines, and solution deployment.
• Understanding how AI/ML, automation, and analytics contribute to operational efficiency and innovation.

Qualifications & Skills:

• Currently pursuing a Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (preferably in 2nd or final year).
• Basic understanding of Python and SQL (academic or project experience).
• Familiarity with Power BI or Tableau is a plus.
• Strong curiosity, willingness to learn, and a problem-solving mindset.
• Good communication and documentation skills.
• Team player with the ability to work in a structured, dynamic environment.

Working Relationship:

• Internal: Collaborate with members of the Data Science & Analytics team and other functional departments as required.
• External: No direct external engagement expected but may observe vendor/partner sessions for exposure.