Help & Supportcareers@gravityer.com
Data Science with less than a year in ML & Deep Learning.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year B.E. student in Artificial Intelligence and Data Science (GPA: 8.7), graduating June 2026. Hands-on experience building machine learning models, deep learning (Convolutional Neural Network / CNN) classifiers, and regression-based prediction systems using Python, TensorFlow, Keras, and Scikit-learn. Proficient in Exploratory Data Analysis (EDA), feature engineering, data pipeline construction, and model evaluation (cross-validation, confusion matrix, RMSE). Certified in MongoDB, Salesforce Agentforce, and Android Development. Skilled in Power BI, Tableau, SQL, Azure, and the full Python data stack. Actively seeking entry-level Data Scientist, ML Engineer, or Data Analyst roles.
SNJB's Late Sau Kantabai Bhavarlalji Jain College of Engineering, Chandwad
Bachelor of Engineering · Artificial Intelligence and Data Science
August 1, 2022 – June 30, 2026
St. Antony Gianelli's Convent Higher Secondary School
Higher Secondary Certificate
N/A – May 31, 2022
Kendriya Vidyalaya
Secondary School Certificate
N/A – May 31, 2020
Netleap IT Training and Solution
Data Science Trainee Intern
January 1, 2025 – February 1, 2025
Nashik, Maharashtra, India
Medical Insurance Premium Prediction
January 1, 2024 – December 31, 2024
Built a regression model (Linear Regression, Ridge, Random Forest) to predict medical insurance premiums on an 8,000-row healthcare dataset; achieved R² score of 0.87 and reduced RMSE by 22% through feature engineering, outlier removal, and cross-validation. Conducted comprehensive Exploratory Data Analysis (EDA) using Matplotlib and Seaborn; identified 5 high-impact features (BMI, age, smoking status, region, children) driving 85%+ of premium variance. Performed hyperparameter tuning using GridSearchCV on Random Forest model, improving prediction accuracy by 12% over the baseline Linear Regression model.
View ProjectAnimal and Object Classification using Convolutional Neural Network (CNN)
January 1, 2023 – December 31, 2023
Designed and trained a Convolutional Neural Network (CNN) deep learning model using TensorFlow and Keras to classify 10 categories of animals and objects from images; achieved 91% test accuracy on a 12,000-image dataset. Built an end-to-end data pipeline: preprocessed images with normalization, resizing (224×224 px), and data augmentation (rotation, flipping, zoom) to reduce overfitting and improve generalization by ~18%. Evaluated model performance using accuracy curves, confusion matrix, and precision-recall metrics; deployed model inference using Python script with batch prediction capability.
View ProjectAgentforce Specialist
Salesforce (Trailhead)
June 1, 2026 – Present
Android Developer Certification
Virtual Internship, AICTE
June 1, 2026 – Present
Android and Flutter Development
Sunanda Infotech Pvt. Ltd.
June 1, 2026 – Present
Soft Skills Certification
GTT Foundation
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internship demonstrate a strong interest and foundational skill set in Data Science, aligning well with the target role. The diversity of projects (image classification, medical premium prediction) and exposure to various ML techniques suggest adaptability and a willingness to explore different problem domains. The certifications, while not all directly related to Data Science, show a proactive approach to learning and skill development. The candidate is a final-year student, which implies a learning-oriented mindset suitable for entry-level roles.
Soft Skills & Operational Fit
The candidate lists problem-solving, analytical thinking, team collaboration, and communication as soft skills. The internship experience mentions collaboration with cross-functional teams, indicating a foundational understanding of operational fit in a team environment. However, without specific assessment data, the depth of these skills cannot be fully evaluated.