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Data Science with less than a year in Machine Learning & AI techniques.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science Intern skilled in Python, SQL, and machine learning algorithms. Experienced in data preprocessing, exploratory data analysis (EDA), feature engineering, and model development using Scikit-learn, TensorFlow, and XGBoost. Proficient in data visualization using Power BI and Streamlit. Knowledge of deep learning, predictive modeling, and AI techniques.
APJ Abdul Kalam Technological University Kerala
B.Tech · Electronics and Communication Engineering
August 1, 2021 – June 30, 2025
Luminar Technolab
Data Science Intern
October 1, 2025 – June 1, 2026
India
Hybrid Log Classification System (Regex + Statistical ML + LLM)
June 1, 2025 – October 1, 2025
Developed a hybrid text classification system to automate real-time log analysis and reduce manual monitoring effort by combining Regex-based rule matching, BERT-based statistical learning, and Qwen LLM routing via Groq Cloud for accurate and cost-efficient classification. Built a production-ready FastAPI backend integrated with a Streamlit dashboard for live inference, confidence monitoring, intelligent model routing, and performance analytics using Python, Transformers, and Scikit-learn.
CardioSense - AI-Based Cardiac Monitoring System
January 1, 2025 – June 1, 2025
Built an AI-powered cardiac monitoring system for ECG anomaly detection, improving model accuracy by 25% through advanced preprocessing and class balancing. Designed a real-time mobile health application with automated alerts, reducing response time for abnormal conditions by 35%.
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a passion for applying AI/ML to real-world problems (log analysis, cardiac monitoring). The use of diverse technologies (BERT, LLM, YOLOv8, FastAPI, Streamlit) indicates a willingness to learn and adapt. The internship experience, though future-dated, shows an understanding of professional environments. The personal projects are well-defined and showcase practical application, which aligns with a proactive and innovative culture. However, the lack of team-based projects or explicit collaboration details limits a deeper cultural fit assessment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems (e.g., hybrid classification system). The focus on reducing manual effort and improving accuracy/efficiency suggests a results-oriented approach. However, without specific behavioral assessment data, it's difficult to fully assess soft skills like teamwork, problem-solving under pressure, or adaptability.