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Data Analyst with less than a year in Data Analytics, Machine Learning & Power BI
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Results-driven Data Analyst with hands-on experience across the full analytics lifecycle from raw data ingestion and SQL-based profiling to ML-augmented quality checks, EDA, and Power BI dashboard deployment. Delivered measurable outcomes including 30% reduction in data inconsistencies, 40% cut in manual reporting effort, and 89% NLP model accuracy across e-commerce and research datasets. Proficient in Python, SQL (PostgreSQL, SQL Server, MySQL), Power BI/DAX, and Scikit-learn; experienced with ETL pipelines, data lake concepts, Azure, and Databricks. Seeking a Data Analyst role to translate complex, high-volume datasets into decision-ready insights that accelerate product and business growth.
MGM University
Bachelor of Technology (B.Tech) · Biotechnology
August 1, 2021 – June 30, 2025
AI Variant
Data Science Intern
January 1, 2026 – Present
Bengaluru, Karnataka, India
RASA Bioinformatics
Data Analyst Intern
June 1, 2025 – December 1, 2025
Pune, Maharashtra, India
NLP Sentiment Analysis – Amazon Product Reviews
June 1, 2026 – June 1, 2026
• Profiled and analysed 10,000+ Amazon review records - vectorised text using TF-IDF and trained SVM classifier achieving 89% accuracy, outperforming Random Forest (76.7%) and Gradient Boosting (74.6%); boosted accuracy 12% over unprocessed baseline via end-to-end NLP cleansing pipeline (tokenisation, stopword removal, lemmatisation). • Deployed a real-time Streamlit web app enabling product teams to classify customer sentiment instantly - scaling from hours of manual review to under 1 second per prediction, with results communicated through a visual dashboard accessible to non-technical stakeholders.
View ProjectCustomer Segmentation using K-Means Clustering & ML
June 1, 2026 – June 1, 2026
• Profiled 2,200+ customer records - identified data quality gaps and behavioural patterns; segmented into 4 cohorts (Premium, Low-Value Families, Store-Oriented, Online) using K-Means with Elbow Method and Silhouette Score validation; applied Random Forest and Logistic Regression to classify segments in real time, reducing manual profiling effort from days to seconds. • Deployed interactive Streamlit dashboard with dynamic Plotly visualisations communicating segmentation results to non-technical marketing teams enabling precision-targeted campaign decisions instantly.
View ProjectCustomer Shopping Behaviour Analysis
June 1, 2026 – June 1, 2026
• Conducted descriptive analytics on 3,900+ retail transactions using Python and PostgreSQL - segmented customers into Loyal (3,116), Returning (701), and New (83) cohorts via 10 structured SQL queries (CTEs, window functions, GROUP BY) answering critical business questions on revenue by gender, discount impact, and top-product performance. • Built Power BI dashboard with 6 KPI visuals reduced stakeholder reporting time by 4 hours per week; delivered 5 data-driven business recommendations including a subscription conversion strategy projected to grow subscriber rate from 27% to 40%.
View ProjectGoogle Data Analytics Professional Certificate
Coursera
June 1, 2026 – Present
Data Science Certification
ExcelR, Pune
January 1, 2026 – Present
Data Analysis & Machine Learning Certification
ExcelR, Pune
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from e-commerce sentiment analysis to customer segmentation and bioinformatics, indicates adaptability and a broad interest in applying data analysis across different domains. Their experience in both personal projects and internships, coupled with continuous learning through certifications, suggests a proactive and growth-oriented individual. The emphasis on delivering measurable business impact aligns well with a results-driven culture. The candidate's current pursuit of a Google Data Analytics Professional Certificate further reinforces a commitment to industry best practices and continuous improvement.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills by identifying business problems and applying data-driven solutions. Their project descriptions highlight an ability to work independently and deliver end-to-end analytical solutions. The focus on reducing manual effort and improving efficiency suggests a results-oriented and operationally aware mindset. The deployment of interactive dashboards indicates an understanding of stakeholder communication and the importance of accessible insights.