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Data Analyst with less than a year in Data Science & Machine Learning
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Assessing your cultural and operational fit
Highly motivated and results-oriented Data Science Intern with a passion for leveraging data to drive business insights. Proficient in Python, SQL, and various machine learning techniques, with hands-on experience in ETL pipeline development, interactive dashboard creation, and advanced analytical modeling. Eager to apply skills in a dynamic environment, contributing to data-driven decision-making and process optimization.
Medi-Caps University
Bachelor of Technology · Information Technology
August 27, 2022 – June 1, 2026
DAKSHABHI IT Solutions Pvt. Ltd.
Data Science Intern
January 6, 2026 – May 10, 2026
India
FinOps Cloud Cost Analysis & Forecasting
June 1, 2026 – Present
Analyzed 260K+ cloud billing and usage records across services, regions, and environments to identify major cost drivers and inefficiencies, with a focus on non-production cost leakage. Conducted in-depth exploratory data analysis (EDA) to uncover service-level and environment-wise spending patterns, revealing disproportionate costs in Development and Staging environments. Engineered time-series features (lag variables, rolling means, seasonality indicators) and built forecasting models to predict monthly cloud costs and support financial planning. Identified a structural cost reduction phase and proposed FinOps-aligned optimization strategies, including auto-shutdown of non-production resources and reserved instance recommendations, delivering actionable business insights.
Credit Card Fraud Detection
June 1, 2026 – Present
Processed 550k+ real-world financial transactions with severe class imbalance, performing data cleaning, handling missing values, outliers and performing feature engineering on 10+ variables to improve model performance. Implemented Logistic Regression and Random Forest models, achieving 85% recall, and performed thorough model optimization and evaluation using AUC-ROC, Precision-Recall, and confusion matrix metrics to ensure robust fraud detection. Applied PCA-based dimensionality reduction 40%, improving computational efficiency for scalable model deployment. Demonstrated real-world fraud detection pipeline design, aligning with enterprise data analytics and monitoring systems.
IBM Data Science Professional
Unknown
June 1, 2026 – Present
IBM Machine Learning with Python
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects cover diverse domains like FinOps, fraud detection, and ERP data analysis, indicating a broad interest and adaptability to different business contexts. Their proactive pursuit of certifications (IBM Data Science Professional, IBM Machine Learning with Python) demonstrates a commitment to continuous learning and professional development, which aligns well with a growth-oriented culture. The detailed descriptions of their contributions and impact suggest a results-driven mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking and problem-solving skills through their project work, particularly in identifying cost drivers and operational inefficiencies. Their experience in designing and deploying dashboards suggests good communication of insights. The project diversity indicates adaptability and a proactive approach to learning and applying new skills. The internship experience shows an ability to work within a structured environment and contribute to business objectives.