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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 You’ll 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.