Rahul Sharma is a project manager with over three years of hands-on experience in machine learning data operations at Amazon’s Alexa Data Services, now leading projects at Sago. He combines operational rigor from his time as an operations manager with deep domain experience in data annotation, defect rate analysis and pilot program execution. Rahul's background bridges technical data workflows and stakeholder-facing program delivery, informed by an MBA in Finance. He has a practical track record of scaling ML data processes and adapting quickly to new project scopes. Based in Delhi, he brings both the discipline of large‑scale operations and the curiosity to iterate on emerging ML data challenges. Colleagues describe him as someone who turns long-tenure experience into continuous learning and measurable process improvements.
3 years of coding experience
5 years of employment as a software developer
Master of Business Administration Finance General, Master of Business Administration Finance General at Rukmini Devi Institute of Advanced Studies
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Contributions:61 pushes, 43 branches in 2 years 5 months
data-qualityspark-mlapacheunitspark
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