Rudransh Madaan

Built a multi-channel lead generation pipeline integrating Apollo, LinkedIn Sales Navigator, Smartlead, AWS SES, and HubSpot. Automated lead extraction, enrichment, CRM synchronization, and reporting using Python with AI-assisted development through Claude Code. Designed automation workflows connecting lead sourcing, AI enrichment, personalized outreach, CRM synchronization, and reporting using REST APIs and cron jobs, significantly reducing manual effort.

Migrated

ClockDiary analytical workloads from SQL Server to Amazon Redshift using Amazon S3 snapshots, reducing query runtime from 10s to 2s while improving reporting reliability.

Data Analyst at APPWRK IT Solutions (2026-01 – Present)

• Built a multi-channel lead generation pipeline integrating Apollo, LinkedIn Sales Navigator, Smartlead, AWS SES, and HubSpot. Automated lead extraction, enrichment, CRM synchronization, and reporting using Python with AI-assisted development through Claude Code.
• Designed automation workflows connecting lead sourcing, AI enrichment, personalized outreach, CRM synchronization, and reporting using REST APIs and cron jobs, significantly reducing manual effort.
• Migrated ClockDiary analytical workloads from SQL Server to Amazon Redshift using Amazon S3 snapshots, reducing query runtime from 10s to 2s while improving reporting reliability.
• Developed Power BI dashboards for the ClockDiary production database, resolving five critical data integrity issues and enhancing activity, device adoption, and subscription analytics.

Data Analyst Intern at Living Things (iCapo Tech Pvt. Ltd.) (2025-06 – 2025-09)

• Designed and deployed 7+ Metabase dashboards using advanced business metrics to improve client reporting and operational insights.
• Automated end-to-end data pipelines, validation and reporting workflows using Python, SQL, AWS Redshift, Metabase and SageMaker, improving reporting efficiency by 30% while supporting analytics dashboards and algorithm validation.
• Diagnosed and resolved device-issue mismatches across 15+ operational categories, collaborating with algorithm teams to implement targeted improvements that increased overall device accuracy by 35%.
• Developed production-grade Python automation scripts and cron-scheduled jobs, reducing execution time by 72%.

Data Science Intern (Concurrent) at Celebal Technologies (2025-06 – 2025-08)

• Developed and evaluated multiple machine learning models using Python and Scikit-learn for academic performance forecasting, improving data quality by 25% through feature engineering and pipeline optimization.
• Optimized SQL-based ETL workflows processing over 3 million transactional records, reducing data redundancy by 22% through schema optimization and improving inference speed by 15%.
• Built a RAG-based loan assistance chatbot using LangChain, improving support efficiency and reducing manual query resolution by 30%.

Frontend Developer Intern at A2IT (2024-07 – 2024-08)

• Developed and deployed 10+ responsive web applications using HTML, CSS, JavaScript and React.js with a focus on usability and performance.
• Built modular frontend components and responsive user interfaces for an e-commerce platform, improving maintainability and user experience.

Bachelor of Technology in Computer Science and Engineering (AI & ML) – Amity University Punjab (2022-09 – 2026-07)