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Fullstack Engineer with less than a year in Data Science & NLP
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Assessing your cultural and operational fit
Data Science and Full-Stack Developer with production deployments at Infosys Springboard and Maximus Atlas. Delivered a live attendance platform serving 50+ employees and an NLP sentiment pipeline aggregating 4 live data sources. Specialized in NLP, LLM integration, FastAPI, and React maintaining a 9.30 CGPA throughout.
Navinchandra Mehta Institute of Technology and Development
Master of Computer Application (MCA)
August 1, 2024 – June 30, 2026
Saket College of Arts, Science and Commerce
Bachelor of Science in Information Technology (BSc IT)
August 1, 2021 – June 30, 2024
Maximus Atlas
Full-Stack Developer Intern
January 1, 2026 – Present
Thane, Maharashtra, India
Infosys Springboard
AI Intern
November 1, 2025 – February 1, 2026
India
Mental Health Sentiment Analyzer
June 24, 2026 – Present
Achieved 87%+ classification accuracy by fine-tuning DistilBERT on a labeled mental health corpus to detect stress, anxiety, and depression indicators from raw user text — outperforming baseline TF-IDF classifiers by ~22%. Boosted inference robustness across varied writing styles by building a multi-step NLP preprocessing pipeline (tokenization, stopword removal, normalization) that sanitized noisy, short-form social content before model input. Shipped a zero-setup Streamlit dashboard visualizing real-time emotional trend charts, making the system fully usable by non-technical users — no coding or ML knowledge required.
Customer Behavior Analysis Dashboard
June 24, 2026 – Present
Reduced business decision lag from days to hours by designing an end-to-end analytics pipeline from raw transactional data to executive-ready KPI dashboards across 5+ relational PostgreSQL tables. Uncovered high-value customer cohorts and revenue leakage by authoring PostgreSQL queries segmenting spending patterns, demographic breakdowns, and CLV metrics — giving stakeholders evidence-backed data for the first time. Delivered 3 Power BI dashboards with dynamic KPIs and drill-through filters showing purchase frequency, customer lifetime value (CLV), and demographic revenue splits — adopted by the business team as the primary reporting tool.
Cultural Fit Analysis
The candidate's profile shows a blend of full-stack development, data science, and AI/ML, which aligns well with a dynamic, innovation-driven culture. The personal projects and internships demonstrate initiative and a continuous learning attitude. The experience in building systems for diverse user groups (HR staff, non-technical stakeholders) suggests an ability to collaborate and communicate effectively across different teams. However, the experience is primarily internship-level, which might require mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving, efficiency improvement, and user-centric design, indicating a strong operational fit. The ability to work on diverse projects (full-stack, AI/ML, data analytics) suggests adaptability and a proactive approach to learning. The focus on delivering tangible business value (e.g., 'reduced business decision lag', 'eliminated 100% of manual HR tracking') demonstrates a results-oriented mindset.