Data Science with less than a year in Machine Learning & Predictive Analytics
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Assessing your cultural and operational fit
Aspiring Data Scientist with hands-on internship experience in machine learning, predictive analytics, and data-driven problem solving. Skilled in Python, SQL, Excel, Power BI, Scikit-learn, TensorFlow, and PyTorch with practical experience in EDA, feature engineering, model evaluation, dashboard development, NLP, and imbalanced data handling. Passionate about building scalable analytical and ML-based solutions. Strong interest in applying machine learning and business analytics to solve real-world challenges through data-driven insights, visualization, and predictive modeling workflows.
Rajasthan Technical University
B.Tech · Computer Science
August 1, 2021 – June 30, 2025
Rubixe.ai
Data Scientist Intern
September 1, 2025 – Present
India
Customer Transaction Prediction
June 21, 2026 – Present
• Developed predictive models on high-dimensional customer transaction dataset with weak signal patterns • Performed EDA, preprocessing, feature analysis, and threshold optimization for recall improvement • Implemented Logistic Regression, Random Forest, and XGBoost models for classification tasks • Achieved ROC-AUC ~0.86 with improved balance between precision and recall
Credit Card Fraud Detection
June 21, 2026 – Present
• Built fraud detection pipeline on highly imbalanced financial transaction dataset containing 280K+ records • Applied SMOTE and preprocessing techniques to improve minority class prediction performance • Evaluated models using ROC-AUC, Precision, Recall, and F1-score; achieved ROC-AUC ~0.97 • Deployed trained ML model using Flask and implemented end-to-end prediction workflow
Flight Fare Prediction
June 21, 2026 – Present
• Built regression models to predict airline ticket prices using feature engineering and exploratory data analysis • Processed temporal and categorical features including duration, airline, stops, source, and destination • Compared Linear Regression, Decision Tree, and Random Forest models for performance optimization • Random Forest achieved R² ~0.79 with strong predictive capability on unseen data
Sales Analytics Dashboard
June 21, 2026 – Present
• Designed interactive dashboard to analyze sales trends, profit distribution, customer behavior, and regional performance • Created KPI-driven visualizations for revenue tracking, category analysis, and business reporting • Performed data cleaning, transformation, and analysis using Python, Excel, and Power BI • Generated actionable business insights to support data-driven decision-making and reporting workflows
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in applying data science to diverse real-world problems, including fraud detection, customer behavior prediction, flight fare prediction, and sales analytics. This breadth of application suggests adaptability and a problem-solving mindset. The ongoing internship at Rubixe.ai further indicates a commitment to gaining practical experience in the field. However, the candidate's experience level is very low (still pursuing a bachelor's degree and in an ongoing internship), which might impact cultural fit for a senior role requiring extensive industry experience and leadership.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end data science workflows, from data cleaning and preprocessing to model deployment and insight generation. The focus on evaluating models with various metrics suggests an analytical and detail-oriented approach. The internship experience, though ongoing, aligns well with practical data science tasks. However, without psychometric test results, specific soft skills like logical reasoning, work attitude, stress handling, and team collaboration cannot be objectively assessed.