Priya Yadav

DATA ANALYST | SQL | EXCEL | PYTHON | DATA VISUALIZATION

Mumbai

Summary

Detail-oriented Data Analyst with 2+ years of experience working with large-scale financial and transactional datasets. Skilled in SQL, data cleaning, data analysis, and reporting to generate actionable business insights. Experienced in building automated reporting systems, optimizing queries, and analyzing customer and transaction data. Strong foundation in statistics and Python with hands-on experience in exploratory data analysis, KPI tracking, and predictive modeling.

Overview

years of professional experience

Work History

SQL Developer (Data Analytics)

Pioneer Infotech (Client: CRISIL Limited)

01.2025 - 07.2025

Processed and validated high-volume financial datasets, ensuring data integrity and accuracy.
Designed data validation rules, improving data quality and reducing errors by 15%.
Built structured datasets used for risk analysis and business reporting.
Improved data traceability and monitoring, helping teams identify inconsistencies quickly.
Supported analytics teams by preparing clean and structured data for analysis.

SDE I - Data Engineering (MIS & Reporting)

M2P Fintech

10.2022 - 01.2025

Analyzed millions of customer and transaction records to generate actionable insights for business decision-making.
Developed and maintained 100+ SQL queries and stored procedures to support reporting and analytics use cases.
Built and automated MIS reports and dashboards, improving reporting efficiency by 40%.
Optimized complex SQL queries, reducing execution time by 75%, enabling faster business insights.
Performed data cleaning and validation to ensure high data accuracy for downstream reporting.
Collaborated with cross-functional teams (product, operations) to support data-driven decision-making.
Assisted in tracking key performance indicators (KPIs) and identifying performance trends.

Education

Masters of Science - Statistics

Mumbai University

Bachelor of Science - Statistics

Ramniranjan Jhunjhunwala College

Skills

Languages & Tools: SQL (SQL Server, Oracle), PythonData Analysis: Data Cleaning, Data Transformation, Exploratory Data Analysis (EDA)Visualization: Basic Excel, Power BI (Learning)Techniques: Statistical Analysis, Hypothesis Testing, KPI TrackingLibraries: Pandas, NumPy, Scikit-learn, Matplotlib, SeabornOther: Reporting Automation, Data Validation, Git

Additional Information

Loan Approval Prediction (End-to-End ML Project)

Performed data cleaning, preprocessing, and feature engineering on financial dataset
Conducted EDA to identify patterns influencing loan approval decisions
Built classification models achieving 0.77 ROC-AUC
Deployed using Streamlit for real-time predictions

House Price Prediction

Conducted EDA and feature transformation
Built regression model with optimized performance using cross-validation

Customer Segmentation

Performed clustering using K-Means
Identified customer segments and derived business insights

Timeline