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Data Analyst with less than a year in analytics, ML, Power BI, and SQL.
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Assessing your cultural and operational fit
Data Analyst with a proven track record of building end-to-end analytics and ML pipelines across Python, SQL, and Power BI. Delivered projects spanning 7,000+ customer records, predictive churn modeling at 81% accuracy, RFM customer segmentation, and multi-page executive dashboards each tied to a measurable business outcome. Skilled at translating ambiguous data into clear, decision-ready insights that drive retention, revenue, and operational efficiency. Seeking internship / entry-level Data Analyst roles at high-growth or product-led organisations where rigorous, scalable analytics work matters.
RKGIT, Ghaziabad
BCA · Computer Applications
August 1, 2024 – June 1, 2027
St. Francis Convent, Bareilly
Senior Secondary (CBSE)
June 1, 2021 – June 1, 2023
SQL Data Cleaning & EDA - Global Layoffs Dataset
January 1, 2023 – January 1, 2024
Cleaned 2,361 layoff records across 20+ industries - resolved duplicates, null values, inconsistent text, and date format issues using a staging table workflow. Conducted comprehensive EDA using CTEs, subqueries, aggregate functions, and window functions to uncover industry-wise and regional layoff trends (2020-2023). Identified that consumer and retail sectors led layoffs, with the US contributing highest records - applicable to workforce planning and economic analysis.
View ProjectCustomer Churn Analysis & Prediction
January 1, 2023 – January 1, 2024
Built end-to-end ML + analytics pipeline on IBM Telco dataset (7,043 records) - data cleaning, EDA, SQL analysis, and feature engineering. Achieved 81.37% prediction accuracy (Precision: 0.70, Recall: 0.58) via Logistic Regression; identified month-to-month contracts and electronic check payments as top churn drivers. Delivered a 4-page Power BI dashboard: Executive Overview, Demographics, Churn Drivers & Revenue Analysis, and ML Insights - enabling C-suite retention decisions. Applied feature importance analysis to surface retention levers: fiber optic users, seniors, and customers lacking tech support showed highest churn probability.
View ProjectE-Commerce Sales & Customer Analytics
January 1, 2023 – January 1, 2024
Analysed 4,000+ real-world e-commerce transactions across customers, products, and countries to surface revenue and behavioural insights. Performed RFM-based customer segmentation - classified customers into VIP, Loyal, At-Risk, and Lost cohorts to prioritise retention and re-engagement strategies. Built interactive Power BI dashboards covering monthly revenue trends, top-performing products by country, and customer lifetime behaviour patterns. Wrote advanced SQL queries for cohort-level aggregations, revenue growth analysis, and customer ranking across segments.
View ProjectData Analytics Bootcamp
Analyst Builder
April 1, 2026 – Present
Advanced Excel Workshop
DUCAT (ISO 9001:2000)
April 1, 2025 – Present
Google Data Analytics Professional Certificate
Google / Coursera
July 1, 2024 – Present
Ask Questions to Make Data-Driven Decisions
Google / Coursera
July 1, 2024 – Present
Python for Absolute Beginners
Udemy
April 1, 2024 – Present
Cultural Fit Analysis
The candidate's projects are well-aligned with a Data Analyst role, covering key areas like data cleaning, EDA, predictive modeling, and visualization. The diversity of projects (layoffs, customer churn, e-commerce sales) shows a broad interest in applying data analytics to different business contexts. The certifications further reinforce a proactive learning attitude. However, all projects are academic, and there is no professional experience, which might indicate a need for mentorship and adaptation to a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems, translate technical findings into business insights, and present data clearly. The academic nature of projects suggests a foundational understanding of data analysis workflows. However, there is no information regarding collaboration, stress handling, or direct work attitude from the provided data.