Data Science with less than a year in ML & Data Analytics
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Assessing your cultural and operational fit
Results-driven aspiring Data Scientist and ML Engineer with hands-on experience in machine learning, deep learning, and data analytics. Proficient in the Python ML ecosystem (Pandas, NumPy, Scikit-learn, TensorFlow, XGBoost) and experienced in building end-to-end ML pipelines, interactive dashboards, and AI-powered applications. Published researcher in AI-powered social media analytics (IRJMETS, April 2026). Pursuing B.E. in CSE (AI & ML) at MGM College, Navi Mumbai (Expected 2027), CGPA 8.00. Seeking a challenging ML Engineer / Data Scientist role to solve complex real-world problems using data-driven and cutting-edge AI approaches.
MGM College of Engineering, Navi Mumbai
B.E. · Computer Science Engineering (AI & ML)
August 1, 2024 – June 30, 2027
Agnel Polytechnic Vashi, Navi Mumbai
Diploma · Artificial Intelligence & Machine Learning
August 1, 2021 – June 30, 2024
Infodeal Technologies
Web Development Intern
June 1, 2023 – July 1, 2023
Pune, Maharashtra, India
Ollama LLM RAG System - Local Retrieval-Augmented Generation
June 1, 2026 – Present
Built a fully local RAG pipeline using Ollama (Llama 3 / Mistral) as the LLM backbone, enabling privacy-preserving document Q&A without external API calls. Integrated ChromaDB as the vector store for semantic document chunking, embedding, and similarity-based retrieval using nomic-embed-text. Developed an interactive Streamlit frontend allowing users to upload PDFs, query documents in natural language, and receive grounded LLM responses with source citations. Optimised context window management and prompt engineering to reduce hallucinations and improve answer faithfulness on custom corpora.
Data-Refinery - Automated Data Cleaning Web App
June 1, 2026 – Present
Built a full-featured Streamlit app for automated data cleaning: missing value imputation, outlier detection, encoding, and feature scaling. Added EDA summary visualizations and one-click cleaned dataset download; reduced manual preprocessing time by ~70% in testing.
Cloud-Based Online Code Compiler
June 1, 2026 – Present
Built a cloud-based platform enabling users to write, compile, and execute code online in Python, Java, and C++. Implemented secure sandboxed code execution using Docker containers deployed on AWS EC2 for scalable performance.
Nova - Multilingual AI Voice Assistant
June 1, 2026 – Present
Developed a multilingual voice assistant supporting English, Hindi, and Marathi with wake-word detection. Integrated web search, weather API, math solver, app launcher, and command execution pipelines into a unified interface.
InsightSphere AI Pro - Social Media Analytics Platform
April 1, 2026 – Present
Built a real-time analytics platform that aggregates and processes social media data with AI-powered insight generation — subject of a peer-reviewed publication (IRJMETS, April 2026). Integrated NLP-driven sentiment analysis and automated reporting pipelines for content strategy decision-making.
InsightSphere AI Pro: A Real-Time Social Media Analytics Platform with AI-Powered Insights
IRJMETS
April 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from social media analytics to LLM RAG systems and data cleaning, indicates a broad interest in various AI/ML applications. Their academic background in AI & ML, coupled with a strong project portfolio, aligns well with a Data Science target role. The candidate's proactive approach to learning and project development suggests a good fit for an innovative and growth-oriented culture. However, the lack of professional experience beyond a short internship means their adaptability to diverse corporate cultures is yet to be fully proven.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and self-learning capabilities, as evidenced by their self-taught advanced Python ML libraries and diverse personal projects. Their internship experience highlights collaboration within an agile team, participation in code reviews, and adherence to sprint schedules, indicating good teamwork and operational fit. The publication and project descriptions suggest a problem-solving mindset and attention to detail.