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Data Science with less than a year in Data Analysis & AI/ML Modeling.
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Final-year Computer Engineering student specializing in LLM applications, agentic AI systems, and data pipelines. Built production-style multi-agent platforms using LangGraph and FastAPI, with hands-on experience in RAG pipelines, prompt engineering, Text-to-SQL systems, and ML modeling. Passionate about delivering reliable, scalable AI solutions for data-driven domains.
PCCOER, Pune
B.E. · Computer Engineering
August 1, 2022 – June 30, 2026
Rajarshi Shahu Jr. College
HSC
June 1, 2020 – May 31, 2022
SV Codetech Solutions
Data Analyst / AI Intern
January 1, 2025 – February 1, 2025
Pune, Maharashtra, India
Insight Agent – Agentic Data Analyst Platform
June 24, 2026 – Present
• Designed and implemented a multi-agent analytical system using LangGraph (Planner → Profiler → EDA → Analysis → Visualizer → Critic), automating end-to-end data analysis workflows from natural-language queries on structured datasets. • Built a production-style FastAPI backend supporting dual execution modes (Notebook Mode + Agentic Workflow Mode) with secure sandboxed execution and session persistence for reliable multi-step reasoning. • Developed AI guardrails via a Critic agent to detect hallucinations, validate outputs, and trigger fallback strategies, improving trustworthiness and auditability of generated insights. • Integrated multi-provider LLM architecture (OpenAI, Gemini) enabling cost-latency optimization and flexible model orchestration across agent workflows.
View ProjectAI-Powered Text-to-SQL Assistant with RAG
June 24, 2026 – Present
• Engineered a RAG-based Text-to-SQL system converting natural-language queries into executable SQL using schema-aware retrieval, significantly reducing hallucinated tables and columns. • Designed a dynamic schema retrieval pipeline with relationship-aware JOIN generation, improving accuracy on complex multi-table queries by ~30%. • Built an interactive Streamlit interface for real-time query generation, SQL preview, and result visualization, enabling seamless non-technical user interaction. • Optimized retrieval strategies and prompt design to balance accuracy, latency, and cost in production-style deployment scenarios.
View ProjectAI-Based Genetic Trait Prediction
June 24, 2026 – Present
• Developed a hybrid deep learning pipeline combining CNN-based sequence feature extraction with XGBoost classifiers to predict genetic traits (T2D, height, baldness) from raw DNA sequences. • Built trait-specific models using encoded genomic windows, improving predictive performance over generalized baseline models across all target traits. • Implemented an end-to-end system covering preprocessing, encoding, training, and probability-based risk scoring for personalized genomic insights.
View ProjectMachine Learning Specialization
Stanford Online & DeepLearning.AI
July 1, 2025 – Present
Google Advanced Data Analytics Professional Certificate
April 1, 2025 – Present
Microsoft Power BI Data Analytics Professional Certificate
Microsoft
March 1, 2025 – Present
Career Essentials in Data Analysis
Microsoft & LinkedIn
March 1, 2025 – Present
Oracle Cloud Infrastructure 2025 Certified Data Science Professional
Oracle
October 1, 2024 – Present
Cultural Fit Analysis
The candidate's projects are diverse, covering genetic trait prediction, agentic data analysis, and Text-to-SQL systems, indicating a broad interest and adaptability. The target role is Data Science, which aligns well with the candidate's project focus and certifications. However, the experience level is very low (0 years, with a brief internship), which might impact immediate cultural integration into a senior-level team without significant mentorship. The projects are all personal, which, while impressive for a student, doesn't fully demonstrate collaborative team dynamics in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an ability to design complex systems. The focus on 'AI guardrails' and 'cost-latency optimization' suggests an awareness of production-readiness and reliability, which are crucial for operational fit. The internship experience, though brief, shows exposure to real-world data analysis tasks and stakeholder communication.