Nalini Chandhi
Principal Engineering Manager @ Microsoft | AI, Cloud Strategy, Master of Data Science
- Role
- Principal Engineering Manager, Artificial Intelligence at Microsoft
- Location
- Dallas-Fort Worth, TX, US
- LinkedIn followers
- 500 followers
About Nalini Chandhi
Nalini Chandhi is a Principal Engineering Manager for Artificial Intelligence at Microsoft, where she provides strategy and technical leadership to the elite specialist community for Microsoft AI services. She is an AI specialist with over 15 years of experience in AI, cloud architecture, strategy, customer engagements, product development, application architecture, data architecture, and analytics.She is passionate about using data science to solve real-life problems and empower customers to achieve their goals. She has managed multiple projects to create proof of solutions and generate business value for customers using Azure Open AI, Azure Machine Learning, Cognitive Services, and Knowledge Mining. She has also contributed to the innovation and adoption of in-memory technology and data lake solutions in her previous roles at Deloitte and SAP.
Experience
Principal Engineering Manager, Artificial Intelligence
Oct 2024 — Present · Dallas, TX, US
Provide strategy and technical leadership to Microsoft elite specialist community for Microsoft AI services - Azure Ai Foundry, Azure Open AI, Azure Machine Learning, Cognitive Services and Knowledge Mining.
Education
UC Berkeley School of Information
Master of Information and Data Science, Data Science
National Institute of Technology Warangal
Bachelor of Technology (B.Tech.), Engineering
Skills
- Abap
- Sap Crm
- Solution Architecture
- Requirements Analysis
- Sap Erp
- Sap
- Sap Netweaver
- Business Analysis
- Soa
- Java
- Business Intelligence
- Business Objects
- Sap Implementation
- Data Modeling
- Requirements Gathering
- Sql
- Software Development
- Erp
- Software Project Management
- Integration
- Data Migration
- Sap Hana
- Data Science
- Big Data Analytics
- Machine Learning
- Api Management
- Hadoop
- Data Lake
- Microsoft Azure
- Exploratory Analysis
- Amazon Web Services (Aws)
- Sap Products
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