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Data Science with 2+ years in Python, SQL & Power BI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven Data Analyst with hands-on experience in Python, SQL, Power BI, and machine learning through internship work and real-world projects. Skilled in data cleaning, exploratory data analysis (EDA), statistical analysis, feature engineering, KPI reporting, ETL pipelines, data visualization, and predictive modeling using tools such as Pandas, NumPy, scikit-learn, and Tableau. Proven ability to analyze datasets, identify trends, and support data-driven decision-making.
Utkal University
Bachelor of Computer Applications (BCA) · Computer Applications
N/A – June 30, 2026
Synent Technology
Data Analyst Intern
April 1, 2026 – May 31, 2026
India
Western Carriers (India) Ltd.
Field Supervisor
December 1, 2021 – November 30, 2023
Jharsuguda, Odisha, India
House Price Prediction
May 1, 2026 – May 31, 2026
Built an end-to-end house price prediction machine learning pipeline using 50,000+ records, achieving R² = 0.9981. Conducted comprehensive EDA, including null checks, duplicate detection, and outlier analysis (IQR method), skewness testing, and correlation heatmaps across 19 features. Applied feature engineering and data transformation techniques, including log transformation and encoding, to improve model performance and reduce prediction error. Trained and compared Linear Regression, Ridge Regression, Random Forest, and Gradient Boosting models using R², MAE, MSE, and RMSE evaluation metrics. Visualized results via Actual vs. Predicted scatter plots and model comparison bar charts for all trained models. Serialized the final trained model using Joblib, achieving R² = 0.9981 and MAE = ₹16,095 on 10,000 unseen test records.
View ProjectSuperstore Sales Analysis
April 1, 2026 – April 30, 2026
Implemented an ETL pipeline in Python to clean raw retail data and created new features, including Days_to_Ship, Profit_Margin, and Unit_Price for deeper business analysis. Modeled a Star Schema with three-dimensional tables and a fact table to optimize data structure. Leveraged advanced SQL techniques, including CTEs, Window Functions, and CASE statements, to analyze sales and profitability trends. Identified the Furniture category as the primary contributor to overall losses despite generating high revenue. Built a five-page Power BI dashboard to track $2.2M in revenue, sales trends, and a -1.3% profit margin.
View ProjectNetflix EDA Analysis
April 1, 2026 – April 30, 2026
Analyzed 8,807 Netflix titles; handled missing values using mode imputation to create a clean and analysis-ready dataset. Extracted time-based features and identified 2019 as the peak content acquisition year with 6,832 titles added during 2017 – 2020. Examined catalog distribution and found that the USA accounted for 32% of total content, while over 75% targeted mature audiences (TV-14 and above). Mapped content strategy across 123 countries, uncovering a 69.6% Movies vs. 30.4% TV Shows split.
View ProjectAssociate Data Analyst in SQL
DataCamp
January 1, 2026 – Present
Microsoft Excel
Code Basics
January 1, 2026 – Present
Power Query, Power Pivot & DAX
Maven Analytics
January 1, 2025 – Present
Data Science & Machine Learning Foundations
Maven Analytics
January 1, 2025 – Present
Python Foundations for Data Analysis
Maven Analytics
January 1, 2025 – Present
Cultural Fit Analysis
The candidate shows a strong initiative in self-learning and project development, which aligns with a proactive and growth-oriented culture. The transition from a non-technical field supervisor role to an aspiring data analyst/scientist demonstrates adaptability and a clear career pivot. The personal projects and certifications indicate a passion for the field and a willingness to acquire new skills independently. However, the lack of team-based data projects or professional experience beyond a short internship limits the assessment of collaboration and professional communication within a data team.
Soft Skills & Operational Fit
The candidate's previous role as a Field Supervisor indicates experience in supervision, operational management, and meticulous record-keeping, which suggests a foundational ability to manage tasks and ensure accuracy. However, direct evidence of collaboration, problem-solving in a data context, or communication skills specific to a data science role is limited to project descriptions.