Shivaay singh Rajput

Results-driven Data Analyst and Python Developer with 2+ years of experience building data pipelines, machine learning models, and end-to-end automation workflows. Founder & CEO of VisionQuantech, delivering AI-powered business intelligence and automation solutions to SMB clients across real estate, healthcare, and retail. Pursuing BS in Data Science from IIT Madras.

Skilled at translating raw data into actionable insights and revenue-generating products using Python, SQL, Power BI, Tableau, Scikit-learn, and TensorFlow.

Founder & CEO at VisionQuantech (VQT) (2023-01 – Present)

• Built LeadLock Pro™ — an AI-powered lead automation system integrating WhatsApp Business API, Make.com, and Calendly — reducing client lead response time by 70% and increasing booking conversion rates for real estate and healthcare SMBs.
• Engineered a Python-based lead enrichment data pipeline that processed 1,200+ raw real estate leads, achieving 85%+ email inference accuracy using pattern-based matching, Pandas, and AI-assisted web scraping.
• Developed real-time data dashboards for lead funnel analytics, enabling clients to track pipeline KPIs, conversion rates, and revenue impact at a glance.
• Designed and deployed end-to-end automation workflows using Make.com and n8n, reducing manual data entry by 60% across client operations.
• Architected a GitHub-to-SaaS conversion framework transforming open-source repositories into deployable products — foundational to the 270+ tool VisionQuantech Business Suite (VBS).
• Managed full project lifecycle — discovery, solution design, delivery, and post-deployment support — operating at 100% gross margin via a client-side tool cost model.

Freelance Data Analyst & Python Developer at Self-Employed (2023 – Present)

• Performed exploratory data analysis (EDA) and statistical modeling on multi-domain client datasets using Python, Pandas, NumPy, and Matplotlib, surfacing key business insights.
• Built Power BI and Tableau dashboards enabling real-time KPI tracking and reducing manual reporting effort by 50% for retail and real estate clients.
• Developed supervised and unsupervised machine learning models — regression, classification, clustering — using Scikit-learn and TensorFlow, achieving 80%+ accuracy on predictive tasks.
• Automated ETL pipelines using Python and SQL for data extraction, cleaning, transformation, and reporting, cutting data processing time by 50%.
• Delivered analytics and automation solutions across real estate, healthcare, and retail verticals, consistently receiving client referrals for quality and speed of delivery.

Bachelor of Science (BS) in Data Science – Indian Institute of Technology Madras (IIT Madras) (2026)