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Data Science with less than a year in machine learning & statistical analysis
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Data Scientist with a background in civil engineering and expertise in Python, machine learning, and statistical analysis. Skilled in deriving data-driven insights for problem-solving, with hands-on experience in data analysis, visualization, and predictive modeling.
ODINSCHOOL
DATA SCIENCE CERTIFICATION / BOOTCAMP
August 1, 2024 – June 30, 2025
Technocrat Institute of Technology, RGPV, Bhopal
Bachelor of Technology · Civil Engineering
August 1, 2018 – June 30, 2022
CUSTOMER CHURN PREDICTION
January 1, 2024 – Present
Built a Random Forest-based customer churn prediction model achieving 84% cross-validation accuracy. Improved prediction reliability by balancing 70:30 class ratio using SMOTE, enhancing recall for churned customers by 18%. Identified key churn factors such as low engagement and longer service tenure. Applied data preprocessing, EDA, SMOTE using Python (pandas, NumPy, seaborn, scikit-learn) to handle imbalance and improve recall.
MOVIE RECOMMENDATION SYSTEM
January 1, 2024 – Present
Built a hybrid recommendation engine using Collaborative and Content-Based Filtering to predict user movie preferences. Performed data preprocessing and feature extraction from movie metadata using Python (pandas, NumPy, scikit-learn). Implemented models using Cosine Similarity and K-Nearest Neighbors, evaluated via RMSE, precision, and recall. Discovered that users with similar viewing patterns often preferred the same genres and directors.
Cultural Fit Analysis
The candidate's background in Civil Engineering followed by a Data Science certification demonstrates a proactive approach to skill development and career change, which can be a positive indicator of adaptability and continuous learning. The academic projects show initiative in applying data science concepts. However, the lack of professional experience or diverse project types beyond academic settings limits the assessment of cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to identify problems, apply relevant techniques, and interpret results, suggesting a problem-solving mindset. The academic background in Civil Engineering combined with a Data Science certification indicates adaptability and a drive for career transition. However, without direct work experience, operational fit regarding team collaboration, project management, and stakeholder communication cannot be fully assessed.