Data Science & Applied AI Internship

Position Overview

We are looking for a motivated Data Science Intern to join our Technology team starting from 1-Oct-2026 and gain hands-on experience in building data-driven solutions for our Decision Intelligence platform. This internship offers an opportunity to learn the fundamentals of data science in a professional environment, working alongside experienced data scientists and machine learning engineers on real-world analytical projects.

Key Responsibilities

• Assist in collecting, cleaning, and organizing data from various internal and external sources to support analytical projects.
• Perform basic exploratory data analysis (EDA) to uncover trends, patterns, and anomalies in datasets under the supervision of senior team members.
• Support the development of statistical models and machine learning experiments by preparing data, running scripts, and documenting results.
• Create simple data visualizations and summary reports to communicate preliminary findings to the team.
• Assist in maintaining data documentation, metadata records, and analytical workflow logs.
• Participate in team meetings, code reviews, and knowledge-sharing sessions to learn best practices in data science.
• Conduct research on data science techniques, tools, and industry trends as assigned by the team.
• Support senior data scientists with ad-hoc data requests, analysis tasks, and project documentation.

Essential Requirements

• Currently pursuing or recently completed a Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Basic knowledge of Python or R programming languages.
• Foundational understanding of statistics and probability concepts.
• Familiarity with data manipulation using libraries such as Pandas or NumPy.
• Knowledge of MS Office, particularly Excel.
• Strong analytical thinking and attention to detail.
• Eagerness to learn and ability to take constructive feedback.
• Good communication skills in English.

Preferred Qualifications

• Completion of relevant coursework or online certifications in data science or machine learning.
• Exposure to SQL and relational databases.
• Familiarity with data visualization tools such as Tableau, Power BI, or Matplotlib.
• Experience with academic or personal data science projects (e.g., Kaggle competitions, capstone projects).
• Basic understanding of version control systems such as Git.