Help & Supportcareers@gravityer.com
Data Analyst with less than a year in Machine Learning & Business Intelligence
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Analyst and Machine Learning graduate with hands-on experience building interactive dashboards, SQL analytics, and predictive models. Skilled in Python, Power BI, Tableau, and large-scale data processing with real-world internship experience delivering data-driven business insights, optimizing databases, and deploying production ML models.
Aditya College of Engineering
Bachelor of Technology · Computer Science and Engineering
August 1, 2021 – June 30, 2025
AI Variant
Data Science Intern
March 1, 2025 – June 1, 2025
Hyderābād, Telangana, India
Blackbuck Engineering
Software Development Intern
January 1, 2025 – April 1, 2025
Hyderābād, Telangana, India
Bankruptcy Prevention Classification System
January 1, 2025 – December 31, 2025
• Developed binary classification model using Logistic Regression and Random Forest predicting bankruptcy probability for 250 companies achieving 87% precision, 91% recall, and 89% overall accuracy • Conducted extensive exploratory data analysis, statistical analysis, and feature importance analysis using Python and SQL, creating interactive Tableau dashboards and reports to visualize key bankruptcy indicators and financial risk factors • Implemented model versioning, A/B testing framework, and automated reporting pipeline to continuously monitor and improve prediction accuracy and model performance across multiple iterations
Customer Segmentation & Analytics System
January 1, 2025 – December 31, 2025
• Performed unsupervised learning using K-Means and hierarchical clustering algorithms to segment 50K+ customers into 5 distinct behavioral groups enabling targeted marketing strategies, personalization, and customer retention programs • Designed comprehensive Power BI and Tableau dashboards presenting customer behavior patterns, RFM (Recency, Frequency, Monetary) analysis, and segment characteristics driving 25% improvement in marketing campaign ROI and customer acquisition • Extracted and transformed large-scale customer data using complex SQL queries with joins, aggregations, and window functions, delivered actionable business intelligence recommendations translating technical findings into marketing strategies
View ProjectHybrid Financial Distress Prediction System
January 1, 2024 – December 31, 2024
• Architected ensemble machine learning model combining Random Forest, Support Vector Machine (SVM), and Voting Classifier achieving 89% accuracy and 0.91 F1-score on financial dataset of 3,672 companies with 86 engineered features • Performed data extraction and transformation using SQL queries and Python, applied Principal Component Analysis (PCA) for dimensionality reduction and K-Means clustering for feature extraction improving model interpretability by 32% • Built comprehensive Power BI dashboard with DAX measures and Power Query for real-time financial metrics visualization and deployed scalable Flask API processing 500+ daily prediction requests with sub-second response time
Machine Learning with Python
Coursera
June 1, 2026 – Present
Cloud Computing
NPTEL
June 1, 2026 – Present
Data Science Certification
ExcelR Solutions
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects cover diverse areas like financial distress prediction, bankruptcy prevention, and customer segmentation, showcasing a broad interest in applying data analysis to different business problems. The combination of data science and software development internships indicates adaptability and a willingness to learn various technical domains. The listed certifications further demonstrate a commitment to continuous learning and skill development, which aligns well with a growth-oriented culture.
Soft Skills & Operational Fit
The candidate's project descriptions highlight collaboration with cross-functional teams and translating technical findings into business recommendations, indicating good communication and teamwork skills. The experience in deploying production-ready models and optimizing performance suggests a results-oriented and problem-solving approach. The academic projects and internships demonstrate a proactive learning attitude and ability to apply theoretical knowledge to practical scenarios.