Data Analyst with less than a year in Data Science & AI
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Highly motivated Computer Science and Engineering (AI) student with a strong foundation in data science, machine learning, and programming. Experienced in developing LLM post-training pipelines, curating datasets, and contributing to real-world AI applications. Proficient in Python, Java, SQL, and various data analysis and visualization libraries, demonstrated through impactful projects in heart disease risk analysis and mental health disorder prediction.
Noida Institute of Engineering & Technology
B.Tech · Computer Science and Engineering (AI)
August 1, 2022 – June 30, 2026
Satyam International School
CBSE Class 12th
June 1, 2020 – May 31, 2022
Bishop Scott Senior Secondary Girls School
CBSE Class 10th
June 1, 2018 – May 31, 2020
Ethara Al
LLM Post Training Intern
March 1, 2026 – May 31, 2026
India
YBI Foundation
Data Science Trainee
October 1, 2024 – November 30, 2024
India
Heart Disease Risk Analysis
June 1, 2025 – June 30, 2025
Analysed a 300+ record clinical dataset; identified chest pain type and resting blood pressure as the strongest predictors of heart disease via correlation analysis. Created a correlation matrix and Identified features strongly related to the target variable. Performed full EDA including distribution analysis, countplots, and histograms across 13 clinical variables to surface patterns in patient health data. Checked distribution of resting blood pressure and understood how blood pressure values are spread.
Mental Health Disorders
March 1, 2025 – March 31, 2025
Explored 4 real-world mental health datasets to analyse prevalence patterns of disorders like depression, anxiety, bipolar, and schizophrenia across different countries and age groups. Performed correlation analysis across 5 mental health disorders and found meaningful relationships between conditions like bipolar disorder and anxiety. Used Linear Regression to explore whether schizophrenia, depression, anxiety, and bipolar disorder rates could predict eating disorder prevalence - achieving 63% model accuracy.
Data Visualisation with Python (90%)
IBM
June 1, 2026 – Present
Introduction to Java Programming (93%)
IBM
June 1, 2026 – Present
Human-Centered Design for Inclusive Innovation(91.66%)
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate an interest in diverse domains (healthcare, mental health), which suggests adaptability. The LLM internship indicates a proactive approach to learning new technologies. However, the experience is primarily academic and internship-based, which might require more structured mentorship in a professional setting to fully integrate into a senior team culture. The breadth of skills (Python, Java, SQL, Power BI) shows a willingness to learn and apply various tools.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work with real-world datasets and apply analytical techniques. The LLM internship suggests an interest in cutting-edge AI, which could be a valuable asset for future growth, but the primary focus of the current target role (Data Analyst) is more on data extraction, transformation, and reporting. The academic nature of projects and limited professional experience mean operational fit for a senior role is currently low.