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Data Science with less than a year in ML, Power BI, SQL, and Python.
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Assessing your cultural and operational fit
Detail-oriented Data Analyst with hands-on experience in Excel, Power BI, SQL, and Python. Delivered end-to-end ML models and operational dashboards that translate raw data into measurable business insights. Certified in Data Analytics (2026) with a proven ability to clean, analyse, and visualise complex datasets to support data-driven decisions.
SNDT Women's University
Bachelor of Computer Applications (BCA)
N/A – June 30, 2023
Car Price Prediction
January 1, 2026 – June 1, 2026
Engineered a Linear Regression model in Python to predict car prices; achieved an R² score of 0.85+ after feature selection and preprocessing on a dataset of 10,000+ records. Executed full EDA pipeline null-value treatment, outlier removal, and feature encoding - reducing data noise and improving model reliability. Leveraged Scikit-learn, Pandas, NumPy, and Matplotlib to build, evaluate, and visualise model performance end-to-end.
House Price Prediction
January 1, 2026 – June 1, 2026
Developed and benchmarked 2 regression models (Decision Tree vs Random Forest) to predict house prices; Random Forest outperformed with a higher R² score, guiding final model selection. Applied feature selection and preprocessing techniques on structured housing data to improve prediction accuracy and reduce overfitting. Produced comparative performance visualisations using Matplotlib to communicate model trade-offs clearly to a non-technical audience.
Swift Route Logistics Dashboard
January 1, 2025 – June 1, 2026
Designed an interactive Power BI dashboard tracking 4 core KPIs — order volume, delivery efficiency, CSAT score, and delay rate — enabling real-time operational monitoring. Built dynamic hub-performance and driver-analysis visuals that identified the top 3 delay-causing drivers and 2 underperforming hubs, directly informing corrective action. Implemented month-wise and year-wise slicers that reduced manual reporting effort and enabled self-serve trend analysis across stakeholders. Highlighted high-usage vehicle models to support fleet optimisation decisions, improving vehicle utilisation visibility.
Data Analytics Certification
Interskill Solutions
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are primarily personal and academic, focusing on core data science tasks like prediction and dashboarding. The diversity of projects (logistics, car price, house price) indicates a broad interest in applying data science across different domains. The target role of Data Science aligns well with the demonstrated skills and project types. However, the lack of professional experience means cultural fit in a team or corporate environment is largely unproven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate raw data into business insights and communicate model trade-offs, suggesting a focus on practical application and stakeholder communication. The projects also show an iterative approach to model development and evaluation.