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Data Science with less than a year in data workflows, ML modeling & visualization.
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Assessing your cultural and operational fit
Aspiring Data Analyst with strong foundation in Data Science and Computer Engineering graduate with hands-on internship experience in end-to-end data workflows including data collection, cleaning, pre-processing, and exploratory analysis. Proficient in Python and its core data stack (NumPy, Pandas, Matplotlib, Plotly) with practical exposure to building predictive models and data visualization pipelines. Developed foundational skills through real-world project work involving structured datasets and ML model development. Eager to contribute analytical thinking and a strong learning mindset to a data-driven team while continuing to grow in the field of Data Science and Machine Learning.
SAL Institute of Technology and Engineering Research
Bachelor of Engineering · Computer Engineering
August 1, 2023 – June 30, 2026
Government Polytechnic Ahmedabad
Diploma · Information Technology
August 1, 2020 – June 30, 2023
Tripada High School
SSC
N/A – May 31, 2020
Infolabz IT Services Pvt. Ltd.
AI/ML Intern
January 1, 2026 – May 1, 2026
Ahmedabad, Gujarat, India
IPL Data Analytics
June 1, 2026 – Present
Built a 4-tab interactive dashboard Overview, Team Analysis, Venue, and Data Assistant on IPL matches dataset. Analyzed team performance trends including season-wise wins, finals appearances, and toss decision impact using Pandas groupby aggregations. Developed venue-based analysis identifying top stadiums, toss patterns, and win/loss ratios across match locations. Implemented a keyword-based Data Assistant for querying top players, highest runs, venue stats, and cup winners.
Zomato Delivery Data Analytics
June 1, 2026 – Present
Built a 4-tab interactive dashboard including Dataset Explorer, Overview, Analytics, and Data Assistant on Zomato delivery dataset. Performed data cleaning and preprocessing on delivery data across city types, weather conditions, and traffic density. Created Plotly visualizations including bar charts, scatter plots, box plots and pie charts to surface delivery trends.
AI-Driven Urban Traffic Congestion Prediction and Mobility Optimization System
June 1, 2026 – Present
Designed and developed an end-to-end ML pipeline to predict urban traffic congestion levels (Low/Medium/High) using real-world structured traffic data from Bangalore. Built a rule-based infrastructure advisory engine recommending grade-separated solutions (flyovers, underpasses, road expansion) based on area-specific physical profiles and corridor congestion metrics. Developed an interactive Streamlit dashboard with Folium maps and Plotly visualizations displaying corridor pressure analysis, congestion heatmaps, and government infrastructure planning support. Implemented an infrastructure strategy validator allowing planners to test and evaluate proposed interventions against real physical constraints of 8 Bangalore urban zones.
Cultural Fit Analysis
The candidate's projects show a diverse application of data science skills across different domains (sports analytics, food delivery, urban planning), indicating adaptability and a broad interest in problem-solving. The focus on building interactive dashboards and end-to-end systems aligns well with roles requiring practical, deployable solutions. The internship experience further solidifies a practical, hands-on approach. The candidate is an aspiring Data Analyst, and the target role is Data Science, which is a good alignment.
Soft Skills & Operational Fit
The candidate demonstrates a strong learning mindset and eagerness to contribute to data-driven teams, as stated in the resume summary. Project descriptions indicate an ability to work on end-to-end solutions, suggesting good problem-solving and project management potential. However, without specific psychometric or English test scores, a detailed assessment of communication, logical reasoning, stress handling, and team collaboration is not possible.