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Data Science with less than a year in Machine Learning & NLP
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Data Analyst Intern with 6 months of experience in AI-powered content automation and text structuring pipelines. Proficient in Python, SQL, and various ML/DL frameworks, with a strong grasp of data cleaning, preprocessing, predictive modeling, and NLP. Adept at building end-to-end data science solutions and delivering high-accuracy models for critical business applications.
Manipal University Jaipur
Bachelor · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Dr Virendra Swarup Memorial Public School
Class XII
N/A – Present
Dr Virendra Swarup Memorial Public School
Class X
N/A – Present
Consecution Co and Tie-ups
Data Analyst Intern
January 1, 2026 – June 1, 2026
Bengaluru, Karnataka, India
Pharmaceutical Inventory Demand Forecasting using Machine Learning
June 24, 2026 – Present
Engineered lag-based (1-3 month) and rolling-window features from 14,700 stock records across 49 medicines and 25 healthcare facilities in 5 states, capturing temporal consumption and depletion patterns. Implemented and optimized a Random Forest regression model using RFE for feature selection and GridSearchCV for hyperparameter tuning, achieving R² = 0.95 (95.37% accuracy) in predicting closing stock levels. Identified consumption, lag-stock, and rolling-mean as top predictive features via feature importance analysis, enabling proactive reorder-point planning to reduce stockout and overstock risk.
View ProjectAutoInsight: Automated EDA & Predictive Modeling Pipeline
June 24, 2026 – Present
Architected an end-to-end automated data science pipeline — validation, cleaning, profiling, target/task inference, modeling, and reporting — deployed as an interactive Streamlit web app. Built rule-based logic to auto-infer the prediction target and task type (classification vs. regression) directly from a natural-language business question and dataset schema. Implemented a Scikit-learn preprocessing pipeline (imputation, scaling, one-hot encoding) to train and benchmark baseline models (Logistic Regression, Random Forest) with task-appropriate metrics (F1, accuracy, R², MAE, RMSE). Auto-generated diagnostic visualizations (missingness, distributions, correlation heatmaps) and a downloadable executive markdown report, with an extensible layer for LLM-based narrative generation.
View ProjectDatabase Programming with SQL
Oracle Academy
June 1, 2026 – Present
Introduction to Machine Learning Specialization
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in practical applications of data science, ranging from inventory forecasting to automated EDA and content generation. This diversity, coupled with an internship, suggests adaptability and a willingness to explore different problem domains. The target role is Data Science, which aligns well with the candidate's project work and stated technical skills. The breadth of skills, including traditional ML, NLP, and LLM integration, indicates a curious and learning-oriented mindset, which is generally a good cultural fit for innovative teams. However, the candidate is still pursuing a Bachelor's degree, which might imply a need for more mentorship and structured guidance in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and an ability to work on complex, multi-faceted tasks. The 'AutoInsight' project suggests an inclination towards automation and efficiency. The internship experience shows exposure to real-world data challenges and pipeline development. However, without direct interview data, assessing specific soft skills like teamwork, leadership, or stress handling is limited.