Udhav Patil

Data Scientist

https://www.opentalent.in/udhav-patil

Run Into The Setting Sun. Run And Suffer. But Don't Mess Up Your Hair!

Mumbai, India

Key Strengths

Demonstrated interest in data analysis and machine learning through personal projects like 'Olympic-Data-Analysis' and 'Movie-Recommender-System'.
Proficiency in Python, Pandas, Seaborn, and Plotly for data manipulation and visualization.
Experience with content-based recommender systems using TMDB dataset.
Exposure to web scraping ('AI-Web-Scraper') and basic application development with Streamlit.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

pulsaar

May 29, 2026 – Present

A beautiful lightweight system monitor widget for macOS, Windows and Linux — built with Tauri + Rust

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100-days-python-Bootcamp

May 25, 2026 – Present

100-days-python-Bootcamp — GitHub repository

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oly-data-analysis

May 6, 2025 – May 6, 2025

oly-data-analysis — GitHub repository

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udhav_135

April 28, 2025 – April 28, 2025

udhav_135 — GitHub repository

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Face-Recognition-Based-Smart-Attendance-System

February 1, 2025 – February 1, 2025

Face-Recognition-Based-Smart-Attendance-System — GitHub repository

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AI-Web-Scraper

February 1, 2025 – May 18, 2025

AI-Web Scrapper

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Emoji-Maze-Adventure-

November 21, 2024 – November 21, 2024

Emoji Maze Adventure is a fun and engaging terminal-based game suitable for all ages! Navigate through a grid of emojis, avoid traps (💀), collect bonuses (⭐), and find the hidden treasure (🎁) before time runs out.

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personal_expense_tracker

November 19, 2024 – November 19, 2024

personal_expense_tracker — GitHub repository

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Olympic-Data-Analysis

March 24, 2023 – May 14, 2025

Olympics Data Analysis Web Application using Streamlit. For development, I will be using Python and Pandas. For plotting, I will be using Seaborn and Plotly libraries.

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Movie-Recommender-System

September 28, 2022 – May 27, 2025

Movie Recommender System is the python Based Project To Create Content Based Recommender System using TMDB 5000 movie dataset from Kaggle

View Project

Key Strengths

Demonstrated interest in data analysis and machine learning through personal projects like 'Olympic-Data-Analysis' and 'Movie-Recommender-System'.
Proficiency in Python, Pandas, Seaborn, and Plotly for data manipulation and visualization.
Experience with content-based recommender systems using TMDB dataset.
Exposure to web scraping ('AI-Web-Scraper') and basic application development with Streamlit.

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards personal learning and exploration, which can indicate a self-starter attitude. However, the projects are predominantly individual and lack explicit team collaboration or diverse industry applications. The 'pulsaar' project with Rust, HTML, JavaScript, and CSS shows some breadth beyond pure data science, but the overall focus is heavily on Python-based data projects. The experience level is 0, suggesting a junior profile, which might not align with senior-level expectations for a Data Scientist role without further validation.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback are available.

Udhav Patil

Key Strengths

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit