Shraddha Singh is a data scientist with eight years of experience building production-ready ML solutions at IBM, currently focused on sustainability use cases in Austin. She blends time-series and anomaly detection expertise with neural forecasting and explainable supervised models to drive operational decisions like energy demand forecasting and materials ordering. Comfortable across the stack, she develops Flask APIs and deploys containerized services on Kubernetes to take models from prototype to client-ready systems. Her background in electrical and computer engineering and prior verification and embedded roles gives her a strong systems perspective that informs robust model design and deployment. She also has a track record of translating exploratory ELK/Python analyses into executive-facing demos and proofs of concept that win stakeholder trust.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Science (B.S.), Electrical and Computer Engineering, 3.7/4.00, Bachelor of Science (B.S.), Electrical and Computer Engineering, 3.7/4.00 at The University of Texas at Austin
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of Technology
Contributions:9 PRs, 107 pushes, 4 branches in 1 year 3 months
iobrokercustom-functions
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