May 2024 – Oct 2024 · 5 mos · Remote

• During my Data Science internship, I gained practical experience working with real-world datasets to uncover insights and support data-driven decision-making. My responsibilities included:
• Collecting, cleaning, and preprocessing structured and unstructured data using Python and libraries like Pandas and NumPy.
• Building and evaluating machine learning models using Scikit-learn for classification, regression, and clustering tasks.
• Visualizing data and model outputs using Matplotlib, Seaborn, and Power BI to communicate insights effectively to stakeholders.
• Collaborating with a team to deploy models and automate data workflows.
• Applying statistical techniques and A/B testing to evaluate business hypotheses and drive strategy.
• This internship solidified my foundational skills in data science and gave me the confidence to solve real-life business problems using data.

Jun 2023 – Jul 2023 · 1 mo · Remote

• Key Responsibilities & Achievements:
• Conducted data collection, cleaning, and preprocessing to ensure high-quality datasets.
• Developed and optimized data models for predictive analytics and business insights.
• Utilized Python, SQL, and data visualization tools Power BI and Matplotlib to analyze trends.
• Implemented machine learning models to improve decision-making processes.
• Automated data pipelines and reporting workflows to enhance efficiency.
• Collaborated with cross-functional teams to translate business needs into data-driven solutions.