Data Analyst with less than a year in Python, SQL, and Power BI
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Detail-oriented Data Analyst and aspiring Data Scientist with expertise in Excel, Power BI, SQL, and Python. Skilled in analysing complex datasets, building interactive dashboards, performing statistical analysis, and applying machine learning fundamentals to generate actionable insights. Experienced in data preprocessing, feature engineering, reporting, and end-to-end analytical workflows that support data-driven business decisions. Strong problem-solving abilities, attention to detail, and a passion for leveraging data to solve real-world business challenges.
Tula's Institute, Dehradun
B.Tech · Computer Science Engineering
August 1, 2021 – June 30, 2025
CBSE
Class XII
June 1, 2021 – May 31, 2021
CBSE
Class X
June 1, 2019 – May 31, 2019
Car Price Data Analysis
January 1, 2023 – January 1, 2024
Cleaned and validated large-scale ex-showroom pricing and transaction datasets; performed EDA to identify spending trends, pricing patterns, and anomalies across categories. Built interactive Power BI dashboards with KPI cards and slicers to support financial reporting; delivered stakeholder-ready MIS reports with actionable pricing and income recommendations. Applied data validation and reconciliation checks to ensure 100% accuracy and consistency; documented analytical findings in structured business reports.
View ProjectHouse Price Analysis
January 1, 2023 – January 1, 2024
Preprocessed large housing and financial datasets - resolved missing values, detected outliers, and corrected inconsistencies to ensure data integrity for downstream analysis. Performed correlation and risk analysis to identify key value drivers (location, area, amenities); produced weekly and monthly MIS reports tracking trends across multiple variables. Visualized spending patterns and data-backed insights with Seaborn and Matplotlib; summarized findings into structured stakeholder presentations for business decision support.
View ProjectHeart Disease Prediction & Risk Analysis
January 1, 2023 – January 1, 2024
Built a binary classification model using feature engineering, hyperparameter tuning, and cross-validation; applied statistical techniques directly applicable to financial risk scoring. Evaluated model performance using accuracy, precision, recall, and F1-score; handled class imbalance to improve generalizability across real-world datasets. Translated quantitative model results into a clear management report with actionable insights and business recommendations - demonstrating ability to communicate analytics to non-technical stakeholders.
View ProjectCultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in data analysis and machine learning, aligning well with a data-driven culture. The diversity of projects (car prices, house prices, heart disease prediction) indicates a broad curiosity and adaptability. The explicit mention of communicating analytics to non-technical stakeholders suggests a team-oriented mindset.
Soft Skills & Operational Fit
The candidate's project descriptions highlight attention to detail, problem-solving abilities, and the capacity to communicate complex analytical results to non-technical stakeholders. These traits suggest a good operational fit for roles requiring clear reporting and collaborative problem-solving.