Key Strengths

Demonstrated interest in Data Science through the 'Cardiovascular-prediction' project.
Experience with Python, a core language for Data Science.
Exposure to machine learning libraries like scikit-learn.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a mix of Data Science and web development (front-end and back-end) projects. While the 'Cardiovascular-prediction' project aligns with a Data Scientist role, the numerous web development projects suggest a broader interest or a less focused career path at this stage. The current role as 'Data Scientist' at Technogigs is a positive indicator, but without details on responsibilities or achievements, it's hard to fully assess alignment. The diversity of technologies (Python, JavaScript, TypeScript, HTML, CSS, Shell) indicates adaptability but also a potential lack of deep specialization in Data Science tools.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, and no other information is available.

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Rhushikesh Nandodkar

Data Scientist

https://www.opentalent.in/rhushikesh-nandodkar

Hello... I am Rhushikesh Nandodkar. I am full stack developer and Machine learning and AI enthusiast.

Technogigs

puneMember since June 12, 2026

https://www.opentalent.in/rhushikesh-nandodkar

Top Skills

Jupyter NotebookHTMLJavaScriptCSSPythontypescriptShell

Skills

Jupyter NotebookHTMLJavaScriptCSSPythontypescriptShell

Experience

Technogigs

Data Scientist

June 12, 2026 – Present

Projects

whynotwebsite

April 10, 2026 – Present

whynotwebsite — GitHub repository

View Project

articulate-ai-front-end

March 16, 2026 – Present

articulate-ai-front-end — GitHub repository

View Project

articualte-ai-backend

March 16, 2026 – Present

articualte-ai-backend — GitHub repository

Cardiovascular-prediction

July 20, 2024 – October 9, 2024

This project involves a machine learning model trained on a dataset of 70,000 individuals, containing various health parameters. The model predicts whether an input patient has cardiovascular disease. Built with scikit-learn, the model utilizes advanced algorithms to achieve accurate predictions based on input health metrics.

View Project

Key Strengths

Demonstrated interest in Data Science through the 'Cardiovascular-prediction' project.
Experience with Python, a core language for Data Science.
Exposure to machine learning libraries like scikit-learn.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, and no other information is available.