Results-driven Data Analyst with 1+ year of hands-on experience in statistical analysis, machine learning, data validation, and business intelligence reporting.
Innovexis
6 mos
Neonsoft Technologies
4 mos
NullClass
5 mos
ExcelR
Jul 2025 – Dec 2025 · India
Performed exploratory data analysis and quantitative analysis on datasets exceeding 100K records, improving data quality and reporting accuracy by 20%; built supervised machine learning models for anomaly detection and predictive analytics with 85%+ model accuracy; conducted root cause analysis and implemented automated data validation and reconciliation frameworks; designed interactive KPI dashboards in Power BI using DAX and Power Query; collaborated with engineering, product, and finance teams; automated ETL workflows and reporting pipelines using Python, reducing manual processing effort by 35%.
Null Class
Aug 2024 – Dec 2024 · India
Executed SQL-based ETL on large relational databases; applied K-Means Clustering for customer segmentation; performed data wrangling and cleaning using Python; supported data reconciliation and compliance reporting workflows, reducing manual errors by 25%; created Power BI and Excel dashboards for non-technical stakeholders.
Bachelor of Technology, Data science
Oct 2021 - Apr 2025
Bachelor of Technology, Data Science
2022 – 2026 (Expected)
CGPA: 7.86 / 10. Relevant coursework: Statistical Analysis, Data Mining, Database Management Systems, Machine Learning, Business Intelligence, Data Modeling, Probability & Statistics, Data Warehousing.
Engineered an end-to-end NLP pipeline for 50K+ customer reviews using VADER and Transformer-based models with 91% classification accuracy; integrated OpenAI GPT API for complaint summaries; developed XGBoost and Random Forest churn prediction with 88% predictive accuracy; applied LDA topic modeling; designed a real-time Power BI dashboard for churn risk, sentiment trends, and customer segments.
Performed EDA and statistical analysis using IBM SPSS and Python; built Logistic Regression and Decision Tree classifiers for credit risk scoring; applied K-Means Clustering for borrower segmentation; designed KPI frameworks and Power BI dashboards for portfolio health, default probability, and risk distribution.