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AI Engineer with less than a year in Data Analytics & Machine Learning.
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Assessing your cultural and operational fit
Recent B.Tech Computer Science graduate skilled in Python, SQL, Data Analytics, Machine Learning, Power BI, Excel, and Business Intelligence. Completed 3+ projects in weather prediction, sales analytics, and recommendation systems. Experienced in data cleaning, exploratory data analysis, dashboard development, KPI reporting, feature engineering, machine learning model development, model evaluation, and Streamlit application development.
Parala Maharaja Engineering College (PMEC)
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
Jawahar Navodaya Vidyalaya
Class X
N/A – May 31, 2019
Jawahar Navodaya Vidyalaya
Class XII
N/A – May 31, 2021
Rooman Technologies Pvt. Ltd.
AI & Data Analytics Intern
February 1, 2026 – May 1, 2026
India
PMEC, Berhampur
Machine Learning Summer Training Program
June 1, 2023 – July 1, 2023
India
Intelligent Book Recommendation System
June 20, 2026 – Present
• Processed and examined 50,000+ user-book ratings and behavioral records using Python, Pandas, and collaborative filtering techniques. • Built a hybrid recommendation engine using Truncated SVD and KNN algorithms to generate personalized recommendations and reduce information overload. • Delivered recommendations from a catalog of 10,000+ books by leveraging dimensionality reduction, similarity analysis, and user preference modeling techniques.
Sales Performance Profit Analysis Dashboard
June 20, 2026 – Present
• Cleaned, transformed, and modeled 5,000+ sales records using Power Query and Excel to create a centralized reporting dataset. • Designed an interactive Power BI dashboard with 10+ KPIs including Revenue, Profit, Orders, Profit Margin, Customer Segmentation, and Year-over-Year Growth analysis. • Developed 15+ DAX measures and advanced visualizations to identify sales trends, regional performance, category-wise profitability, and business growth opportunities.
India Weather Rainfall Prediction System
June 20, 2026 – Present
• Processed and preprocessed 10,000+ weather records using Python, Pandas, NumPy, Label Encoding, and Feature Engi-neering techniques to improve data quality and prediction performance. • Built and evaluated 4 machine learning models (Random Forest, Decision Tree, Logistic Regression, and KNN), achieving up to 89% • Developed an interactive Streamlit application enabling real-time rainfall prediction, data visualization, and automated weather-based decision support.
View ProjectCultural Fit Analysis
The candidate's academic projects cover diverse areas like recommendation systems, sales analytics, and weather prediction, showcasing a broad interest in applying AI/ML to different domains. The inclusion of 'Agentic AI' and 'LLM' in their skills, despite being a recent graduate, indicates an interest in emerging AI technologies, which is a good fit for an AI Engineer role. The academic background in Computer Science & Engineering further strengthens this fit. The internship experience, though short, shows an engagement with industry practices in data analytics. The overall profile suggests a motivated individual keen on applying and expanding their AI/ML knowledge.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems, process large datasets, and develop interactive applications. The academic projects and internship experience suggest a proactive learning attitude and a foundational understanding of data science and machine learning workflows. The focus on clear metrics (e.g., 89% accuracy, 10+ KPIs) in project descriptions suggests an outcome-oriented approach. However, without direct behavioral assessment, specific soft skills like teamwork, problem-solving under pressure, or adaptability cannot be fully evaluated.