Summary
Elaheh Dastan is a Senior Data Scientist with 7+ years of hands-on experience building and deploying production ML systems across mobility, finance, and healthcare domains. She has led end-to-end ML projects—most notably an ETA forecasting platform at Snapp! that improved R2 by 20% across five cities and a large-scale pipeline processing 4M rides/day—combining time series forecasting, MLOps, and real-time monitoring. Adept in TensorFlow, PySpark, MLFlow, Airflow, Kafka and Kubernetes, she has boosted inference performance with ONNX, automated drift detection and slashed train/deploy times by 70% through robust CI/CD and data infrastructure. Her background includes high-accuracy forecasting (90%+ in previous roles), edge deployments using TensorFlow Lite, and practical engineering like a Golang benchmarking microservice that accelerated QA. With an MS in AI and a curiosity that fuels both dancing and chess, Elaheh blends strategic product focus with deep technical execution to deliver measurable business impact.
6 years of coding experience
8 years of employment as a software developer
Amirkabir University of Technology
English, Persian