Help & Supportcareers@gravityer.com
Data Science with less than a year in data analysis & predictive modeling
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven Master's in Business Analytics graduate (CGPA: 3.7/4.0) with hands-on experience in data analysis, predictive modeling, and business operations. Skilled in transforming complex datasets into actionable insights using Python, SQL, and Power BI. Proven ability to manage multiple tasks, communicate findings to stakeholders, and drive data-informed decision-making. Seeking a Business Analytics role to contribute analytical expertise and deliver measurable business value.
Sacred Heart University
Master of Science · Business Analytics
August 1, 2023 – June 30, 2025
Savitribai Phule Pune University
Bachelor of Business Administration
August 1, 2019 – June 30, 2022
Indis Corporate
Sales Associate - Intern
September 1, 2022 – May 1, 2023
Hyderābād, Telangana, India
Analysis of Population in Indian Cities
June 24, 2026 – Present
Analyzed Cities_R2.csv dataset to identify the top 25 most populated Indian cities and examined 0-6 age group demographics, revealing Greater Mumbai (12M+) as the highest populated. Visualized population distributions and demographic trends to surface insights with implications for education and social services planning. Compared literacy rates and demographic composition across top cities to identify regional development patterns.
Comparative Analysis of Decision Tree and Random Forest Classifiers for Business
June 24, 2026 – Present
Built classification models on a biomedical voice dataset (UC Irvine ML Repository) to discriminate healthy individuals from those with Parkinson's disease using optimal feature combinations. Compared Decision Tree and Random Forest performance using information gain and ensemble learning, visualizing results with Seaborn heatmaps. Applied feature engineering on vocal measurements (MDVP:Fo(Hz), Jitter, Shimmer) to maximize classifier accuracy and reduce misclassification rates.
Heart Attack Analysis and Prediction Using Machine Learning
June 24, 2026 – Present
Developed end-to-end ML pipeline on a Kaggle dataset including data preprocessing, EDA, and PCA to identify critical heart attack risk factors. Built and evaluated multiple predictive models to accurately assess a patient's likelihood of experiencing a heart attack, supporting proactive healthcare decisions. Applied encoding of categorical variables and principal component analysis to reduce dimensionality and improve model generalization.
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data science concepts. The diversity of projects (population analysis, disease prediction, heart attack prediction) shows a breadth of interest in applying analytical skills to different domains. The Master's in Business Analytics indicates a strategic alignment with using data for business value. However, the lack of professional data science experience limits the assessment of cultural fit in a fast-paced, industry-specific data science team.
Soft Skills & Operational Fit
The candidate's previous internship as a Sales Associate involved client documentation review, task tracking, report preparation, and stakeholder coordination, indicating foundational organizational, communication, and attention-to-detail skills. These experiences suggest an ability to manage tasks, adhere to deadlines, and contribute to operational efficiency, which are transferable to a data science role requiring project management and stakeholder communication.