About this role
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.