Rahul R.

Data Analyst @Wiliot

San Mateo, CA, US

Machine Learning: Worked on feature engineering, model evaluation, and parameter tuning to improve robustness of tree-based models designed to detect object location changes across multiple sites.• Signal-Based Movement Detection: Developed statistical models using EWMA with dynamic variance, Kalman Filters, and T-Test–based methods to infer object movement from noisy large-scale datasets (100m+) of Bluetooth Low Energy signals. Scaled to national deployment across 4500+ sites. Co-developed a Bayesian Markov Model deployed at 200+ sites, contributing to model architecture and deployment strategy.• Dashboarding & Monitoring: Built and maintained 20+ Tableau and Databricks dashboards for real-time monitoring of ML models, infrastructure health, and experimental KPIs across nationwide deployments.• Analytics Repository: Designed and implemented standardized functions for sample size estimation, incorporating clustering effects and Cohen adjustments, and confidence interval calculation using bootstrapping, t-tests, and binomial tests in the internal analytics library, enabling efficient experiment planning across the team.• Workflow Optimization: Optimized large-scale data jobs (100M+ rows) through SQL/PySpark query optimization, migrating workflows from Pandas to PySpark, and identification of redundant internet gateways, improving latencies and lowering deployed infrastructure costs.• Field Experimentation & Deployment: Led data validation and analytics for large-scale warehouse infrastructure pilots, tracking over 100 million objects/year to develop a blueprint for future nationwide deployments.• Tools & Technologies: Python, PySpark, SQL, Tableau, Databricks, Git.

University of Oxford

Master of Engineering - MEng, Biomedical/Medical Engineering

University of California, Davis

Master of Science - MS, Business Analytics