Nikita Kumari Hembrom

Python / SQL – CrateDB Intern

https://www.opentalent.in/nikita-kumari-hembrom

Bhubaneswar, indiaMember since July 27, 2025

Key Strengths

Strong academic background with a Master of Science in Data Science and Bachelor of Science in Computer Application.
Demonstrated foundational programming skills in Python, R, C, C++, and SQL.
Practical experience in machine learning algorithms (Logistic Regression, KNN, Naive Bayes, Random Forest) through a credit card fraud detection project.
Proficiency in data visualization and relevant tools (Pandas, Scikit-Learn, Jupyter Notebook, Seaborn, Matplotlib).
Project experience includes data preprocessing, model evaluation (Precision, Recall, F1-Score), and achieving high accuracy (98%) in a relevant domain.
Participation in a 'Data Science using Python' workshop indicates a proactive approach to learning and hands-on experience with tools like Google Colab.
The candidate's skills in Python and SQL align directly with the 'Python / SQL – CrateDB Intern' target role.

Cultural & Operational Fit

Cultural Fit Analysis

Based on the psychometric test score of 29% (147/500), which evaluates work attitude, stress handling, and team collaboration, the candidate demonstrates a low cultural fit according to these metrics. This suggests potential challenges in adapting to a collaborative and demanding work environment.

Soft Skills & Operational Fit

The candidate self-reports interpersonal skills such as teamwork, adaptability, presentation skills, management, and quick learning. However, the psychometric test score (29%) indicates significant potential weaknesses in logical reasoning, work attitude, stress handling, and team collaboration, which contradicts the self-assessment and suggests a potential mismatch in operational fit.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Key Strengths

Strong academic background with a Master of Science in Data Science and Bachelor of Science in Computer Application.
Demonstrated foundational programming skills in Python, R, C, C++, and SQL.
Practical experience in machine learning algorithms (Logistic Regression, KNN, Naive Bayes, Random Forest) through a credit card fraud detection project.
Proficiency in data visualization and relevant tools (Pandas, Scikit-Learn, Jupyter Notebook, Seaborn, Matplotlib).
Project experience includes data preprocessing, model evaluation (Precision, Recall, F1-Score), and achieving high accuracy (98%) in a relevant domain.
Participation in a 'Data Science using Python' workshop indicates a proactive approach to learning and hands-on experience with tools like Google Colab.
The candidate's skills in Python and SQL align directly with the 'Python / SQL – CrateDB Intern' target role.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit