Data Science & AI/ML specialist — building SQL-driven reporting pipelines, predictive models, and full-stack dashboards. National Finalist at Insightfy 6.0 (IIM Lucknow), Rank 1 in the Data Analysis Round.
Computer Science Engineering student at MIT Academy of Engineering, Pune. Specialising in Data Science, AI/ML, and Full-Stack Development — with a focus on turning raw data into actionable business decisions.
Completed 2 industry internships in AI engineering and financial analytics, plus a live deployed project (JobSearchy) serving real users. National Finalist at Insightfy 6.0 (IIM Lucknow), Rank 1 nationally in the Data Analysis Round.
I enjoy taking ideas from notebook to production — whether that's a transformer-based caption generator, a customer-upgrade propensity model, or a live job-hunting platform with automated reporting.
End-to-end Python + SQL job-hunting agent. Scrapes 500+ jobs from 7 sources, scores each against your resume with TF-IDF, and delivers automated reports. Click the live preview below, or open it in a new tab.
End-to-end Python + SQL data platform that scrapes 500+ jobs from 7 sources, scores each using TF-IDF cosine similarity against a user's resume, and delivers ranked reports via email and Telegram. SQLite backend with normalised schemas. Flask backend with 15+ REST endpoints powering a React dashboard. Automated 4×-daily scheduler. Currently live in production on Render with 1,480+ jobs indexed.
Comprehensive EDA on 844 Bengaluru restaurants across 8 localities. Cleaned and standardised raw Zomato data; applied 5 statistical tests across 15 visualisations to uncover pricing, rating, and locality-level patterns. Key finding: price has near-zero correlation with customer ratings (r = −0.01). Delivered actionable recommendation: HSR Layout as the top untapped market opportunity.
End-to-end ML classification pipeline on 1,000+ customer records (18 behavioural & demographic features) predicting membership-upgrade propensity. Applied SMOTE for class imbalance; benchmarked Logistic Regression, Random Forest, and XGBoost — final model achieved AUC-ROC of 0.7969. Used SHAP values for per-customer feature attribution. Engineered propensity score buckets driving an estimated ₹33K annual revenue uplift.
Transformer-based computer vision + NLP pipeline that generates natural-language captions for any image. Vision Transformer (ViT) encoder extracts image features; GPT-2 decoder generates fluent captions. Built using Hugging Face VisionEncoderDecoderModel — an advanced architecture over conventional CNN+RNN approaches. Deployed end-to-end with a Gradio interface for real-time image upload and instant captioning.
A tightly crafted, role-targeted resume covering my data analytics & AI/ML work, BB Advisory internship, and the Insightfy 6.0 national finals. Updated regularly — always the latest version.
Rushikesh consistently delivered clean, production-ready analytics work during his internship with us. His Python data pipelines were a standout — fast, readable, and impressively well-automated.
His Insightfy 6.0 submission stood out for both technical rigour and business storytelling. Ranking first nationally in the Data Analysis round is a strong signal of his analytical depth.
Open to data analytics, data science, and AI/ML roles. Based in Pune — available for remote and on-site opportunities across India. I reply within 24 hours.