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Data Science with less than a year in Machine Learning & Data 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 strong skills in Python, SQL, Machine Learning, and Data Analysis. Experienced in data preprocessing, exploratory data analysis (EDA), feature engineering, and building predictive models to extract meaningful insights from complex datasets. Passionate about solving real-world problems using data-driven approaches and delivering actionable business insight.
DHB Soni College Solapur
Bachelor of Entire Computer Science · Computer Science
January 1, 2020 – January 1, 2024
Cognifyz Technology
Data Science Internship
December 1, 2025 – May 31, 2026
India
Online Payments Fraud Detection
July 1, 2025 – December 31, 2025
Developed a machine learning model to detect fraudulent online payment transactions using Python, Pandas, NumPy, Scikit-learn, and XGBoost. Performed data preprocessing and cleaning to handle missing values and prepare the dataset for analysis. Conducted exploratory data analysis (EDA) to understand transaction patterns, identify unusual behaviors, and analyze relationships between features. Applied feature engineering techniques to improve model performance and split the dataset into training and testing sets for validation. Implemented the XGBoost classifier to classify transactions as fraudulent or legitimate and evaluated the model using accuracy, ROC-AUC score, and classification metrics. The model successfully detected fraudulent transactions and demonstrated the effectiveness of machine learning techniques in identifying suspicious financial activities.
Ecommerce Product Delivery Prediction
January 1, 2025 – June 30, 2025
Built machine learning models to predict on-time delivery for an international e-commerce company. Preprocessed data, performed exploratory analysis, and engineered features to improve model accuracy. Developed and compared classification models, including Logistic Regression, Decision Trees, and Random Forest. Delivered visualizations and a comparative analysis of algorithm performance. Outcomes: Improved prediction accuracy by 15%, with the Decision Tree Classifier achieving the highest accuracy of 69%, optimizing delivery schedules and logistics operations. Enhanced customer satisfaction with more reliable delivery timelines and provided valuable insights for resource allocation and operational efficiency.
Data Science And Ai
Boston Institute of Analytics
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a practical application of data science skills to diverse problems (e-commerce delivery prediction, fraud detection, recommendation systems). This breadth of application suggests adaptability and a willingness to tackle various challenges, which could contribute positively to cultural fit. The internship experience further indicates an ability to work in a structured environment. However, the overall experience level is entry-level, which might require more mentorship and integration into a senior team.
Soft Skills & Operational Fit
The candidate's resume highlights a passion for solving real-world problems using data-driven approaches, which suggests a problem-solving mindset. The project descriptions indicate an ability to work through the full lifecycle of a data science project, from data preprocessing to model evaluation. However, without specific psychometric test results or interview data, it is difficult to fully assess soft skills like teamwork, stress handling, or communication clarity in a collaborative setting.