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Data Science with less than a year in machine learning, deep learning, and data visualization.
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 professional with strong expertise in data analysis, machine learning, deep learning, and data visualization. Experienced in building predictive models and interactive applications using Python and modern tools to solve real-world problems and derive meaningful insights.
Mary Matha College of Arts & Science, Madurai Kamaraj University
M.Com CA
August 1, 2023 – June 30, 2025
Mary Matha College of Arts & Science, Madurai Kamaraj University
B.Com CA
August 1, 2020 – June 30, 2023
ML, DL & Streamlit Based Predictive Analytics and Data Visualization Tool
June 19, 2026 – Present
Built an interactive web application to perform predictive analytics and visualize insights from data. Used machine learning models (XGBoost, Scikit-Learn) and deep learning (LSTM) for prediction, with visualizations powered by Plotly.
Multi-Model Bone Fracture Detection System
June 19, 2026 – Present
Developed an AI-powered system to detect bone fractures from X-ray images using multiple models. Implemented deep learning (CNN, ResNet) and machine learning (Random Forest) for accurate classification and comparison of results.
Data Science Certification & Internship
Elysium Academy, Theni
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects are primarily academic, focusing on core data science applications like predictive analytics and image classification. This aligns well with a foundational role in Data Science. However, the lack of diverse project types (e.g., industry-specific, open-source contributions) and limited professional experience suggests a need for exposure to varied team dynamics and real-world business challenges. The target role alignment is good for an entry-level position, but the breadth of skills needs expansion beyond academic projects for senior roles.
Soft Skills & Operational Fit
The candidate lists several soft skills including Analytical Thinking, Problem Solving, Communication, Team Collaboration, Time Management, and Adaptability. While these are relevant for a Data Science role, there is no objective assessment data to validate these claims. The academic nature of projects suggests a foundational understanding of problem-solving within structured environments.