Rahul Sangole is a Sr. Data Science Manager based in Cupertino with 11 years of hands-on experience building forecasting and anomaly-detection systems, now leading data science at Apple. He combines a strong engineering background in mechanical and systems modeling with a Northwestern degree in Predictive Analytics and a Six Sigma Black Belt to bridge rigorous statistical methods and production-grade software. Rahul has a track record of productionizing time-series models, R packages and reproducible Docker workflows to inform finance and cloud services decisions at scale. Previously he led analytics teams at Cummins, turning telematics signals into actionable prognostics and operational savings while codifying best practices for exploratory work versus production code. He actively teaches data literacy as a Carpentries instructor, reflecting a commitment to mentorship and reproducible practices that improve team delivery. Less obvious: his early engineering work—finite element models and CFD—gives him a rare ability to translate physical-system intuition into robust data-driven solutions.
11 years of coding experience
15 years of employment as a software developer
Master's degree Mechanical Engineering, Master's degree Mechanical Engineering at University of Michigan
Master's degree Predictive Analytics, Master's degree Predictive Analytics at Northwestern University
Bachelor's Mechanical Engineering, Bachelor's Mechanical Engineering at Savitribai Phule Pune University
Contributions:4 commits, 3 pushes, 1 branch in 2 years 5 months
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