Shashank Tyagi

Data Scientist at CREATOR OS

Engineered a scalable, GCP-hosted data ingestion pipeline using Python to extract and process creator insights from Instagram Graph API and TikTok API, enhancing data accessibility and supporting real-time analytics across marketing platforms. Developed and deployed a predictive ML model via FastAPI to forecast creator rate cards using performance and engagement metrics, automating pricing decisions and reducing manual analysis time by 70%. Delivered campaign ROI forecasting system using regression models to predict engagement outcomes, optimizing marketing spend efficiency by 25%.

Data Scientist at CREATOR OS (United Kingdom)

Engineered a scalable, GCP-hosted data ingestion pipeline using Python to extract and process creator insights from Instagram Graph API and TikTok API, enhancing data accessibility and supporting real-time analytics across marketing platforms. Developed and deployed a predictive ML model via FastAPI to forecast creator rate cards using performance and engagement metrics, automating pricing decisions and reducing manual analysis time by 70%. Delivered campaign ROI forecasting system using regression models to predict engagement outcomes, optimizing marketing spend efficiency by 25%.

Data Analyst Lead (Part-time) at KLYRR

Led the enhancement of lead conversion processes by designing and deploying supervised machine learning models (Random Forest, Logistic Regression) for lead scoring, resulting in a 15% increase in conversion rates. Automated end-to-end data pipelines to deliver timely and accurate portfolio management reports, significantly reducing manual effort and turnaround time.

Data Analyst Lead (Part-time) at KLYRR

Led the enhancement of lead conversion processes by designing and deploying supervised machine learning models (Random Forest, Logistic Regression) for lead scoring, resulting in a 15% increase in conversion rates. Automated end-to-end data pipelines to deliver timely and accurate portfolio management reports, significantly reducing manual effort and turnaround time.

Data Analyst Intern at KLYRR

Analyzed multi-source datasets to create lead scoring models, improving qualification and prioritization of prospects. Applied data analytics techniques to support marketing and sales efforts, contributing to overall business growth.

AI/ML Trainee and Research Associate at Global Info Ventures

Led the development and deployment of a real-time PPE violation detection system, achieving a 15% reduction in workplace accidents related to PPE non-compliance. Developed and deployed a real-time multi-person face detection algorithm with 95% accuracy for improved attendance tracking, enabling efficient and accurate employee check-in. Analyzed multi-sourced datasets to create lead scoring models, increasing the conversion rate of qualified leads by 15% and driving a 30% lift in content engagement for a new series. Developed lead scoring models and benchmarks that enhanced the marketing-qualified leads conversion rate by 15%, helping the sales team prioritize outreach to the most promising prospects.

AI/ML Trainee and Research Associate at GLOBAL INFOVENTURES

Developed and deployed a real-time PPE (Personal Protective Equipment) violation detection system using computer vision and edge AI (OpenCV, TensorFlow) to identify safety non-compliance on industrial sites. Automated attendance and workforce monitoring through multi-person face detection and recognition models, achieving 95% accuracy across challenging lighting conditions and improving operational efficiency by 30%.