Data Science Intern

We are looking for a Data Science Intern to support data preparation exploratory analysis and basic modelling work. This internship is suitable for a student who enjoys solving problems with data and wants hands-on experience with Python SQL and real-world datasets.

Make an Impact by:

• Collect clean and organize data from different sources.
• Perform exploratory data analysis to identify trends patterns and data quality issues.
• Write basic SQL queries to extract and transform data for analysis.
• Prepare datasets for dashboards reports and machine learning experiments.
• Help build and evaluate simple statistical or machine learning models under guidance.
• Create clear charts summaries and documentation to communicate findings.
• Automate repetitive data preparation or reporting tasks using Python where appropriate.
• Document assumptions data definitions and analysis steps for review and reuse.

Skills for Success:

• Currently pursuing a degree or diploma in Data Science Computer Science Statistics Mathematics Engineering Business Analytics or a related field.
• Basic knowledge of Python and SQL with willingness to apply them in a business setting.
• Familiarity with data cleaning exploratory analysis and basic statistics.
• Comfortable working with spreadsheets or structured datasets.
• Good attention to detail when checking data accuracy and assumptions.
• Able to explain findings clearly and ask questions when requirements or data are unclear.
• Curious self-motivated and keen to learn from feedback.

Preferred Skills

• Exposure to Python libraries such as pandas NumPy scikit-learn matplotlib or similar tools.
• Basic understanding of machine learning concepts such as regression classification clustering or model evaluation.
• Familiarity with data visualization tools such as Power BI Tableau or Python visualization libraries.
• Basic knowledge of Git or version control.
• Interest in applying data science to business customer network operations or digital use cases.

What Youll Gain

• Hands-on exposure to real-world data science and analytics projects.
• Practical experience using Python and SQL in a professional environment.
• Experience working with data quality checks exploratory analysis and business datasets.
• Exposure to how data insights are translated into business recommendations.
• Guidance from experienced team members and opportunities to build applied data work.