Job Description

A Data Scientist Intern assists in analyzing large datasets, building predictive models, and extracting actionable insights to support data-driven decision-making. This role involves working with machine learning algorithms, data visualization tools, and statistical techniques to solve real-world business problems.

Key Responsibilities

1. Data Collection & Preprocessing

• Gather data from databases, APIs, web scraping, and external sources.
• Clean and preprocess data by handling missing values, duplicates, and inconsistencies.
• Perform feature engineering to enhance model performance.

2. Exploratory Data Analysis (EDA)

• Use Pandas, NumPy, and Matplotlib/Seaborn to analyze trends and patterns.
• Apply statistical methods (e.g., correlation analysis, hypothesis testing) for insights.
• Identify key variables that impact business outcomes.

3. Machine Learning & Predictive Modeling

• Train and evaluate machine learning models using scikit-learn, TensorFlow, or PyTorch.
• Work on classification, regression, clustering, and recommendation models.
• Tune hyperparameters and improve model accuracy.

4. Data Visualization & Reporting

• Create interactive dashboards and reports using Power BI, Tableau, or Matplotlib.
• Develop charts, graphs, and heatmaps to communicate insights effectively.
• Present findings to business stakeholders in a clear and actionable manner.

5. Big Data & Cloud Computing (Optional)

• Work with large datasets using Hadoop, Spark, or Google BigQuery.
• Deploy models on cloud platforms like AWS, Google Cloud, or Azure ML.

6. A/B Testing & Decision Support

• Conduct A/B testing to compare different strategies and optimize performance.
• Assist in real-time analytics and business intelligence projects.

Key Skills Required

Technical Skills:

✅ Programming Languages: Python (Pandas, NumPy, Scikit-learn), R.
✅ Databases & SQL: MySQL, PostgreSQL, MongoDB.
✅ Machine Learning: Regression, Classification, Clustering, NLP, Deep Learning.
✅ Data Visualization: Matplotlib, Seaborn, Power BI, Tableau.
✅ Big Data & Cloud Computing (Optional): Spark, Hadoop, AWS, GCP, Azure.
✅ Version Control: Git, GitHub, GitLab.

Soft Skills:

✔️ Analytical Thinking: Ability to interpret and extract insights from complex data.
✔️ Problem-Solving: Applying machine learning techniques to solve business problems.
✔️ Attention to Detail: Ensuring data accuracy and integrity.
✔️ Communication: Presenting insights in a simple and actionable format.
✔️ Time Management: Handling multiple datasets and meeting deadlines.