AI Engineer with less than a year in Data Science & Machine Learning
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As an engineer proficient in Data Science and Machine Learning with a strong foundation in Python, SQL, and Power BI for data analysis and visualization. Proficient in ML techniques such as Regression, Classification, Clustering, and Model Evaluation. Strong foundation in OOP concepts – Encapsulation, Inheritance, Polymorphism, and Abstraction. Passionate about AI, Deep Learning, and NLP. Possesses a strong background in business strategy, data analysis, and project management with a focus on enhancing efficiency and fostering collaboration within cross-functional teams.
SNJB's KBJ College of Engineering, Nashik - Pune University
Bachelor of Engineering · Computer Engineering
December 1, 2021 – June 1, 2025
Garud Junior College, Shendurni
Higher Secondary School
July 1, 2019 – June 1, 2021
Garud School, Shendurni
Secondary School
June 1, 2018 – March 1, 2019
IKIONE Pvt. Ltd.
AI Developer Intern
November 1, 2025 – Present
Pune, Maharashtra, India
MAXGEN TECHNOLOGIES Private Limited
Data Science & Machine Learning Intern
December 1, 2023 – January 1, 2024
Pune, Maharashtra, India
Stroke Prediction Model – Patient Health Classification
June 23, 2026 – Present
Developed a stroke prediction model to predict the likelihood of stroke based on patient health data. Utilized Kaggle's Brain Stroke Dataset containing 5,109 records and 12 features including age, gender, hypertension, work type, and BMI. Performed data preprocessing: handled missing values, removed duplicates, corrected data types, and encoded categorical variables. Conducted EDA and visualized key insights using Seaborn and Matplotlib to identify trends and correlations. Applied SMOTE for class imbalance handling; built and evaluated Logistic Regression, Random Forest, and XGBoost models using accuracy, precision, recall, F1-score, and AUC-ROC.
Agri Smart - Soil and Crop Management System
June 23, 2026 – Present
Design a Soil and Crop Management System using ML, Deep Learning, and real-time weather data to classify soil types, recommend crops, and suggest fertilizers. Collected soil images (Alluvial, Black, Clay, Red) for soil type classification; gathered nutrient (N, P, K, pH) and weather datasets. Applied Random Forest Classifier for crop recommendation and a rule-based + ML model for fertilizer suggestions based on nutrient deficiencies. Designed a Streamlit dashboard with modules for Crop Recommendation, Fertilizer Suggestion, Soil Health Report, and Crop Calendar.
Schema Design and Implementation for Hospital Database Analysis
June 23, 2026 – Present
Design and implement a relational database schema for efficient management of hospital data using MySQL. Identified key entities: Patients, Doctors, Nurses, Appointments, Treatments, Medicines, Billing, and Departments. Developed an ER Diagram and implemented relationships using primary and foreign keys; built queries for patient details, doctor schedules, and treatment history.
Automated Interview Bot for Hiring Process Optimization
June 23, 2026 – Present
AI-enabled Interview Bot that automates candidate assessment using Machine Learning and NLP. Automated interview scheduling, dynamic question generation (technical and behavioural), and multi-modal response analysis via NLP, webcam face detection, and microphone voice input. Generated feedback and performance ratings for candidates; supported three user classes: Candidates, Recruiters, and Administrators.
Cultural Fit Analysis
The candidate's academic projects and internship experiences demonstrate a strong interest and foundational skill set in AI and Machine Learning, aligning well with an AI Engineer role. The diversity of projects, from healthcare prediction to agricultural management and an interview bot, shows adaptability and a broad application of AI/ML concepts. The current internship as an AI Developer Intern further solidifies this alignment. However, the experience level is entry-level, which might require more mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on diverse tasks, from data collection and preprocessing to model building and dashboard design. The experience with MCP Server-Client architecture suggests an understanding of modular design for scalability. However, without specific psychometric or English test scores, it's difficult to assess logical reasoning, work attitude, stress handling, or team collaboration directly. The project descriptions are clear, suggesting good written communication.