Artificial intelligence
Data and analytics professionals in Artificial intelligence
Explore how data professionals decide what information matters for AI projects and when they stop trusting their data. Learn which metrics guided real product choices, what made them question their data quality, and how they handled situations where more data didn't improve decisions.
Professionals to explore
01—10Abhishek Prabhakar
LinkedInExperience: Manager Data and Analytics AI · EY
Experience managing data and analytics AI initiatives and applying data science and generative AI methods within a professional services firm.
Aniruddha Mukherjee
LinkedInExperience: VP - Lead Quantitative Analytics Specialist (AI-COE) · Wells Fargo
Experience leading quantitative analytics and AI center of excellence work at a large financial institution, including data science and AI architecture roles.
Deepak Trehan
LinkedInExperience: Director, Data and AI · BJ's Wholesale Club
Experience leading a team of AI and data engineers, owning enterprise data science strategy and analytics delivery across multiple business functions.
Lalitha Reddy Kotha
LinkedInExperience: Principal Architect (Gen AI Data Science) · Elevance Health
Experience building production-grade machine learning systems and analytics platforms, applying generative AI, data science and cloud AI tools to business decisions.
Rajeev Kumar
LinkedInExperience: Director - Head of Data · Maersk | Artificial Intelligence, Generative AI, and Data ecosystem (Cloud)
Experience directing data, AI/ML and generative AI functions, and leading data science and data architecture practices across consulting and healthcare organizations.
Saurabh Srivastava
LinkedInExperience: Director -Data Analytics & AI · Infosys Limited
Experience directing data analytics and AI work, described as an AI champion practicing generative and agentic AI within a data analytics leadership role.
Sebastian Antinome
LinkedInExperience: Director of Business Analytics · Microsoft
Experience leading a data science and AI engineering team supporting commercial business functions, infusing generative AI into internal processes and platforms.
Shilpa Yelamaneni
LinkedInExperience: Vice President, AI and Data - Global Functions · GSK
Experience leading AI and data strategy as a vice president, with a background spanning data science, advanced analytics, and business intelligence leadership roles.
Sridhar Ramaswamy
LinkedInExperience: AI Principal Data & Analytics Practice Lead · Caterpillar Inc.
Experience leading a data and analytics practice focused on AI product strategy, including edge AI applications and analytics solution development.
Tania Nashelly García Álvarez
LinkedInExperience: Data, Analytics & IA Director for Retail & CPG · Cognodata
Experience directing data and analytics strategies and artificial intelligence initiatives, connecting business objectives with AI-driven technological solutions.
Choose the right perspective
Look for candidates who have owned decisions about which data to use in AI systems. Ask them to describe specific moments when they realized their data had limits or when they chose not to rely on certain metrics. Avoid those who only discuss data collection or reporting without connecting it to actual business choices.
Questions to take into the conversation
- 01Tell me about a time you decided not to use data you had available. What made you distrust it?
- 02Which metric or dataset did you rely on that later turned out to be misleading for your AI product?
- 03When did you realize you needed different data than what you were collecting, and what did you do?
About this directory
This is a professional research starting point based on business profile data retrieved on . Titles and companies reflect that source snapshot and may describe past or present roles. Check the linked profiles for current details. Inclusion does not imply Instant Expert membership or availability.
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