Key Strengths

Demonstrated interest in various machine learning algorithms through personal projects (XGBoost, SVM, Neural Networks, Random Forests, Decision Trees, KNN, Naive Bayes).
Experience with Jupyter Notebook for data science projects.
Focus on practical applications of machine learning for problem-solving (e.g., Parkinson's Disease Detection, Fake News Detection).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal assignments, indicating a foundational understanding of various ML algorithms. However, the lack of team-based projects, diverse technologies beyond Jupyter Notebook, and professional experience (only freelance with no details) makes it difficult to assess cultural fit for a collaborative senior role. The experience level is listed as 0, which contradicts the 'Freelance Data Scientist' role, suggesting a potential mismatch for a senior position.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

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Santhosh C

Data Scientist

https://www.opentalent.in/santhosh-c

Data scientist in the making, traveller and an artist. Like to travel and meet new people and recently got into coding and datascience.

Freelance

IndiaMember since June 13, 2026

https://www.opentalent.in/santhosh-c

Top Skills

Jupyter Notebook

Skills

Jupyter Notebook

Experience

Freelance

Data Scientist

June 13, 2026 – Present

Projects

Parkinsons-Disease-Detection

November 14, 2021 – November 14, 2021

What is Parkinson’s Disease? Parkinson’s disease is a progressive disorder of the central nervous system affecting movement and inducing tremors and stiffness. It has 5 stages to it and affects more than 1 million individuals every year in India. This is chronic and has no cure yet. It is a neurodegenerative disorder affecting dopamine-producing neurons in the brain. What is XGBoost? XGBoost is a new Machine Learning algorithm designed with speed and performance in mind. XGBoost stands for eXtreme Gradient Boosting and is based on decision trees. In this project, we will import the XGBClassifier from the xgboost library; this is an implementation of the scikit-learn API for XGBoost classification. Detecting Parkinson’s Disease with XGBoost – Objective To build a model to accurately detect the presence of Parkinson’s disease in an individual. Detecting Parkinson’s Disease with XGBoost – About the Python Machine Learning Project In this Python machine learning project, using the Python l

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FakeNews-Detection