Tailorcv
Python, FastAPI, JavaScript, PostgreSQL, HTML, CSS
Co-developed and scaled an AI resume-optimization platform to 16,000+ users across 30+ countries and 150+ daily active users, owning the full stack in Python/FastAPI on Neon PostgreSQL — ATS scoring, resume tailoring, portfolio hosting, cover letters, and AI mock interviews. Built the core ATS scoring and resume-tailoring engine — a deterministic 100-point audit across 22 weighted checks, an AI rewrite validated against the candidate's original document to block invented employers, dates, or metrics, and PDF link-annotation recovery that preserves every project, GitHub, and certification URL intact — rendering cleanly across 22 ATS-safe templates without layout breakage. Integrated dual payment rails to serve a global user base — Razorpay for domestic customers and Polar for international — alongside usage quotas, plan gating, and subscription lifecycle handling. Shipped a Chrome extension that tailors resumes directly on job postings across 15 job boards (LinkedIn, Indeed, Naukri, Greenhouse, Lever, Workday), cutting per-application tailoring from ~10 minutes to under 60 seconds; automated end-to-end testing with Playwright. Instrumented the platform for reliability and growth with Sentry error monitoring, GA4 + PostHog analytics, transactional email over SMTP, and one-click portfolio publishing to Netlify.
Myntra E-commerce Website Clone
HTML, CSS, JavaScript
Developed a frontend clone of the Myntra e-commerce platform, implementing product listings, navigation components, and interactive UI using HTML, CSS, and JavaScript. Built dynamic features such as product browsing and cart functionality using JavaScript with DOM manipulation for real-time user interactions. Designed a responsive user interface with structured layouts and modern styling to replicate real-world e-commerce website design patterns.
Customer Behaviour Analytics
Python, PowerBI, SQL, Excel
Executed end-to-end data analysis using Python (Pandas) to clean and explore 3,900 transaction records, handling inconsistent data, and generating result statistics to inform business decisions. Performed complex data querying using SQL to extract actionable insights, including identifying high-spending discount users, calculating average review ratings for top products, and comparing revenue contributions between subscribers and non-subscribers to support targeted marketing strategies. Developed an interactive Power BI dashboard to visualize customer segments and purchasing patterns, revealing that 'Loyal' customers (3,116 individuals) generate the highest revenue and that express shipping correlates with a 3.5% higher average transaction value compared to standard shipping. Delivered data-driven recommendations by identifying top revenue-generating age groups and 5 discount-dependent products (e.g., 50% of Hat purchases used a discount) to optimize pricing and marketing strategies.