About
Highly analytical and results-driven Computer Science (Data Science) student with a strong foundation in machine learning, data visualization, and statistical analysis. Eager to leverage practical experience gained from impactful projects and a data science internship to solve complex problems and drive data-informed decisions in a dynamic tech environment. Possessing a solid understanding of Python, SQL, and AI/ML frameworks, I am committed to contributing to innovative data solutions and advancing my expertise in the field.
Work
→
Summary
Collaborated on data analysis and model development to derive actionable insights and predict customer behavior.
Highlights
Conducted comprehensive exploratory data analysis (EDA) on diverse customer datasets, identifying key trends and presenting actionable insights that informed strategic decisions.
Collaborated effectively within a 5-member team to clean and preprocess large, unstructured datasets using advanced Python libraries (Pandas, NumPy), ensuring data integrity and readiness for analysis.
Contributed to the early-stage development of a machine learning model for customer churn prediction, directly supporting efforts to enhance customer retention strategies.
→
Summary
Provided critical logistical and technical support to ensure seamless execution of major tech events.
Highlights
Supported comprehensive logistics and managed live technical setups for major tech events, ensuring seamless operation and minimizing disruptions.
Managed high-volume communications during peak periods, coordinating with multiple stakeholders to maintain efficient event flow and attendee satisfaction.
Education
Skills
Languages
Python, Java, SQL, HTML, CSS.
Tools & Libraries
Pandas, NumPy, Scikit-learn, OpenCV, Tableau, Power BI, Jupyter, VS Code.
AI/ML
Supervised Learning, Unsupervised Learning, Neural Networks, NLP.
Databases
Snowflake, MongoDB.
Platforms
GitHub, Excel.