Summary
Aditya Rajagopal is a Staff Applied Scientist based in San Francisco with 10 years of experience building and scaling machine learning systems for revenue management in aviation. He combines deep-learning research with pragmatic engineering—driving novel models (including batch-constrained offline RL and RNN-based forecasts) that produced multi-million dollar uplifts and measurable A/B test gains. At FLYR he helped build core data science infrastructure and a modular Python/Keras/TensorFlow framework that accelerated experimentation and reduced deployment friction. He mentors and structures onboarding for junior scientists, runs stakeholder-facing model reviews and workshops, and created decision-quality metrics that tie model outputs directly to revenue and passenger forecasts. Comfortable across BigQuery/Polars, Vertex AI workflows, and production tooling, he also has roots in computer vision, embedded systems and robotics from earlier research and internships. Notably, he engineered lightweight CLI tooling to override model features remotely, shaving valuable time off deployments while preserving reproducibility.
9 years of coding experience
6 years of employment as a software developer
Master of Science - MS Computational Science and Engineering, Master of Science - MS Computational Science and Engineering at Georgia Institute of Technology
Indian Institute of Technology Bombay
English, Hindi, Marathi, Tamil