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AI Engineer with less than a year in Python, Machine Learning & Data Analytics
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Detail-oriented Data Analyst & Machine Learning Engineer with a Master's in Computer Applications (MCA) and hands-on proficiency in Python, SQL, Power BI, and scikit-learn. Experienced in building end-to-end machine learning pipelines, performing RFM customer segmentation, and deploying interactive ML web applications using Streamlit. Skilled in transforming raw datasets into actionable business insights through predictive modelling, advanced visualizations, and data-driven decision-making. Familiar with Generative AI concepts including LLMs, Prompt Engineering, and RAG pipelines. Seeking a Data Science / AI-ML Engineer role with exposure to end-to-end ML pipelines, GenAI applications, and LLM-based systems.
Modern College of Engineering, Pune
Master of Computer Applications (MCA)
August 1, 2023 – June 30, 2025
Yogeshwari Mahavidyalaya, Ambajogai
Bachelor of Science
August 1, 2020 – June 30, 2023
Crowned Concept
Web Development Intern
January 1, 2025 – May 1, 2025
Noida, Uttar Pradesh, India
Behavioral Price Sensitivity Engine
June 1, 2026 – Present
Built an end-to-end ML pipeline on the Online Retail II dataset (1M+ transactions, 5,878 customers) to predict whether a customer will exceed the median spend threshold of $898.92, achieving 83.84% accuracy using Logistic Regression. Applied RFM feature engineering and K-Means clustering (K=3) with the Elbow Method to segment 5,878 customers into High, Medium, and Low Value groups; identified LogFrequency as the strongest predictor (44.7% RF feature importance). Deployed a live Streamlit web application with 5 interactive chart tabs (Probability, Price Sensitivity, Feature Impact, Feature Importance, Model Comparison), auto-loading trained pickle models for real-time predictions and business pricing recommendations.
Steam Game Analytics Dashboard
June 1, 2026 – Present
Analyzed a dataset of 50,000+ Steam game records to evaluate global market trends, pricing strategies, and platform popularity. Developed complex DAX measures to track Key Performance Indicators (KPIs), identifying a 15% higher engagement rate in multiplayer genres. Designed an interactive dashboard with dynamic slicers and drill-through features, enabling stakeholders to filter insights by release year and publisher.
Travel Booking Revenue Analysis
June 1, 2026 – Present
Architected a relational database to manage 10,000+ booking records, ensuring data integrity through Normalization (3NF) and structured schemas. Wrote optimized SQL queries using Joins, Subqueries, and Window Functions to analyze booking trends, revenue streams, and customer preferences. Improved query execution time by 40% by implementing indexing strategies, stored procedure refactoring, and data pipeline integrity checks for uninterrupted reporting operations.
Excel and Copilot Fundamentals
Microsoft
June 1, 2026 – Present
Speaking Effectively
NPTEL / IIT
June 1, 2026 – Present
Data Science and Analytics with AI
Unknown
June 1, 2026 – Present
AI Infrastructure and Operations Fundamentals
NVIDIA
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards data science and machine learning, aligning well with an AI Engineer role. The diversity of projects (price sensitivity, game analytics, travel booking) indicates a broad interest in applying data-driven solutions across different domains. However, the experience is primarily academic and personal projects, with limited professional experience in a dedicated AI/ML role. The certifications in AI and data science further support their interest and commitment to the field.
Soft Skills & Operational Fit
The candidate demonstrates a detail-oriented approach, as evidenced by their project descriptions focusing on specific metrics and methodologies. Their ability to build interactive dashboards and web applications suggests good problem-solving and user-centric design skills. The internship experience in web development indicates an ability to integrate backend data into frontend components and translate technical information for non-technical users, which is valuable for operational fit.