Graduate Intern

# Data Science Intern

## About the Role

We are looking for a motivated and analytical **Data Science Intern** to join our team. The intern will work on real-world data science and data engineering problems, gaining hands-on experience in data analysis, data quality, machine learning concepts, and AI-assisted development.

The ideal candidate should have a strong foundation in **Python, statistics, data analysis, and machine learning**, along with a curiosity to understand business problems and translate them into data-driven solutions.

## Key Responsibilities

* Analyze and explore large datasets to identify patterns, trends, anomalies, and data quality issues.
* Perform data preprocessing, cleaning, transformation, and feature engineering.
* Develop and evaluate statistical and machine learning models under the guidance of senior team members.
* Support the development of data quality and data scoring solutions.
* Work with structured and semi-structured data from multiple sources.
* Create scripts and utilities for data analysis and validation.
* Assist in defining data benchmarks, metrics, and validation criteria.
* Participate in experimentation and evaluation of AI/ML approaches.
* Collaborate with Data Scientists, Software Engineers, and Product teams to understand requirements and solve real-world problems.
* Document analysis, findings, methodologies, and results clearly.
* Leverage modern AI-assisted development tools responsibly to improve productivity and accelerate experimentation.

## Required Qualifications

* Pursuing or recently completed a degree in **Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field**.
* programming knowledge in **Python**.
* Good understanding of:

* Statistics and probability
* Data structures and algorithms
* Data analysis and visualization
* Basic machine learning concepts
* Experience with libraries such as **Pandas, NumPy, and Scikit-learn**.
* Basic understanding of SQL and relational databases.
* Strong analytical and problem-solving skills.
* Ability to learn new technologies and concepts quickly.

## Good to Have

* Exposure to machine learning or deep learning projects.
* Experience with data visualization tools or libraries such as Matplotlib, Seaborn, or Plotly.
* Familiarity with cloud platforms such as AWS, Azure, or GCP.
* Knowledge of data quality, data profiling, or data governance concepts.
* Experience working with APIs or large datasets.
* Exposure to Generative AI or Large Language Models.
* Experience using AI coding assistants such as GitHub Copilot or similar tools.
* Participation in academic, personal, or open-source data science projects.

## What We Look For

* **Strong analytical thinking** and the ability to break down complex problems.
* **Curiosity and willingness to learn** beyond academic concepts.
* Ability to ask the right questions and understand the problem before jumping to a solution.
* **Ownership and accountability** for assigned work.
* Ability to work collaboratively with cross-functional teams.
* Good communication skills and the ability to explain technical concepts clearly.
* A practical mindset and willingness to experiment, learn from failures, and iterate.

## Education

Bachelor’s or Master’s degree in:

* Data Science