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Profile

Software Developer with strong experience in backend systems, automation, and applied machine learning. Proven expertise in web crawling, distributed systems, document pipelines, and secure data delivery using TypeScript, Kafka, Redis, React.js and Python. Adept at collaborating with senior stakeholders while independently owning implementation.

Professional Experience
Junior Analyst (Software Developer), Institutional Shareholder Services Stoxx
Jul 2024 – present
  • Engineered a dynamic, scalable, autonomous web crawling company crawling system, reducing processing time from 30+ days to under 3 days in TypeScript using BFS traversal with Kafka-driven orchestration and Redis process sync, having over 95% targeted document retrieval.
  • Boosted classification accuracy by 20% using regex-based parsing on filename, anchor text, and surrounding Text around Link context by parsing DOM during crawling for documents from websites.
  • Refactored internal TypeScript downloader with bulk URL support, lazy Chrome instantiation, and failure tracking — reducing download overhead by 40%.
  • Added TTL caching to the Java Parser process of crawlers, reducing API requests by 80%, improving throughput.
  • Integrated password-protected Excel generation using native Java in feeds, improving client security while eliminating paid libraries.
  • Revamped API documentation and fixed a critical bug which resulted in NULL Exceptions in Services introduced during Java Services Migration and observability tooling, accelerating developer onboarding, reducing misconfigurations, and mishits on APIs.
  • Managed Kubernetes infrastructure across multiple clusters and namespaces, handling deployments, monitoring pod health, and automating YAML generation and rollout processes using tools like K9S and Kustomize
  • Designed dashboard for 5+ applications to track their statuses and messages in the redis queue using React.js for frontend.
  • Software Developer Intern, Arcon
    Jun 2023 – Aug 2023
  • Broadened knowledge of ARCON Privileged Access Management (PAM) and onboarding automation with Selenium tools
  • Optimized existing APIs reducing access time of response utilizing caching for faster retrievals by 10%
  • Worked on automation of provisioning and de-provisioning of user accounts similar to Single Sign On like Okta, and Google
  • Junior Machine Learning Engineer (Intern), Juppiter AI Labs
    Aug 2022 – Nov 2022
  • Collaborated with a cross-regional team in deploying high-performing email monitoring script using Azure OCR, NLP,and Email SMTP with successful execution rate of 85% on AWS EC2 instance.
  • Pioneered the creation of over 25 immersive Hands-On Labs, Capstone projects, and their corresponding Unit Tests, amplifying the learning experience for KnowledgeHub's(UpGrad) esteemed MLOps course
  • Skills
    Programming Languages — Python, JavaScript, Java, C++|Development — React.js, Node.js, Express, Kafka, FastAPI, Flask, MongoDB, Redis, Postgres, HTML, CSS|Machine Learning — LLMs, Scikit-learn, Tensorflow, Pandas, Numpy, OpenCV, Matplotlib|Tools — Kubernetes, Docker, AWS, BeautifulSoup, Selenium, K9S, Git, Jenkins, MS Office
    Education
    Dwarkadas J. Sanghvi College of Engineering, B.Tech - Computer Engineering (Data Science), Honors in Computational Finance
    2020 – 2024
  • CGPA - 9.63, Interdepartment Badminton Team Captain and Tournament Winner
  • Projects
  • Built a scalable Promotion Engine, where I worked on the frontend with React.js and integrated it with Node.js backend for coupon verification and generation, and ML-based customer analysis using Apriori algorithm. The application also includes a Flutter SDK Integration, and an intuitive admin page, resulting in an increase in coupon redemption rates for small and large-scale companies
  • Ecosense Remote Sensing, Python, Remote Sensing, Multithreading, Deep Learning
  • Real-time data pipeline using remote sensing and satellite imagery to monitor vegetation and predict deforestation in an area over the years. Applied image processing to process satellite data stream with thread architecture, showing accurate vegetation percentage of place and geo-mapping of terrain. Technologies utilized for this are Python, GIS, OpenCV, remote sensing, and parallel computing.
  • Achievements / Positions of Responsibilities
  • 1st Place Winner at Intercollege Hackathon conducted by TIAA out of 20+ teams representing their college. [Github]
  • 1st Place Winner at LOC 5.0, 24 hour Hackathon organized by ACM, DJSCE [Github]
  • Second Runner Up in Doceree and TechGig Machine learning Hackathon from over 3000+ participants [Github]
  • Second Runner Up in Unscript Rookie Machine Learning Hackathon, conducted by FCRCE [Github]
  • 550+ Problem solved on Leetcode [Profile]
  • Vice-Chairperson Tech at DJS Compute - Organizing hackathons and workshops, catering to 1200+ participants. Mentored and Led a team of over 50+ students to conduct lectures, seminars by industry experts, and workshops on notable topics like Machine Learning, MLOps, Competitive Programming, App, and Web Development.