Summary
Hinna Shabir is a data scientist with 11 years of experience who turns messy datasets into actionable insights across Health Tech, Ed Tech, and Sustainability. She has driven measurement frameworks and production reporting that improved ROAS for multimillion-dollar pharma campaigns and led statistical work that reduced survey outliers by 30%, improving patient activation metrics. Comfortable across Python, SQL, Spark, and cloud stacks, she builds end-to-end solutions from exploratory analysis and A/B testing to time-series churn models used for targeted interventions. Her background spans consulting at Deloitte to hands-on research optimizing protein–ligand queries and combinatorial algorithms, reflecting a rare mix of applied industry impact and algorithmic research roots. Based in Vancouver, she’s passionate about ethically applying AI to improve care and retention while translating technical findings for business stakeholders.
11 years of coding experience
9 years of employment as a software developer
M.S, Computer Engineering, M.S, Computer Engineering at University of California, Riverside
B.Eng, Electronics and Telecommunication, B.Eng, Electronics and Telecommunication at Maharashtra Institute of Technology
English, Hindi