​​Hi! I'm Sundeep, an AI leader and consultant with 15+ years of experience in USA, UK, France, India, across Big Tech (Conversational AI at Amazon Alexa), Startups (Applied AI at Swiggy) & Academia (Neuroscience at Oxford [Sir Henry Wellcome Fellow, MSc], UCL [PhD]).

I consult tech companies and leaders on AI Strategy & Product; coach candidates for Big Tech Data Science jobs; blog on AI & Leadership; research on AI & Neuroscience (40+ papers, 2200+ citations); give keynote talks; and the media has extensively covered my work.
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I help Tech leaders & companies build their AI Strategy, Roadmap & Products

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I have advised global clients from US/UK/EU etc. on:
  • Data Science team building strategy for unicorn startup
  • ​NLP for information extraction from Legal documents
  • Sentiment Analysis of Tweets and effect on Stock Price
  • Caption generation for Fashion images in eCommerce
  • Entity extraction from Patent applications
  • Credit scoring based on Blockchain​
  • AI Fairness and Bias Mitigation 

I coach aspiring Data Science professionals to get jobs in Big Tech

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My clients have received Data & Applied Scientist offers from:​
  • Apple
  • Meta
  • Amazon
  • LinkedIn
  • Twitter
  • ​Databricks
  • ​& many more!

I create and share expert AI content and advice
  1. How to Improve Retention in Engineering Teams?
  2. How to hire Data Science teams?​
  3. The Case for Reproducible Data Science​
  4. How to Generate Synthetic Data for Machine Learning Projects
  5. Choosing a Data Governance Framework for your Organization
  6. Surefire Ways to Identify Data Drift 
  7. ​Effective Communication between Scientists and Non-scientists
  8. ​​Data Labeling and Relabeling in Data Science                                                      
  9. Understanding and Measuring Data Quality
  10. The Metric Layer and how it fits into the Modern Data Stack
  11. Team Development Tips for Engineering and Product Leaders
  12. Five 5-minute Team-Building Activities for Remote Teams
  13. ​​Benefits of FAANG companies for Data Science & ML roles
  14. Why Data Democratization is important to your business?
  15. When is the right time to migrate to Kubernetes?
  16. How to ensure Data Quality through Governance
  17. Data Labeling: The Unsung Hero Combating Data Drift
  18. ML Engineer vs Data Scientist
  19. Knowledge Distillation: Principles, Algorithms & Applications                
  20. Best Practices for Improving Machine Learning Models                           
  21. Developing AI/ML Projects for Business - Best Practices                        
  22. How to build AI Teams that Deliver?                                                                  
  23. Why Corporate AI Projects Fail? Part 1/4                                        
  24. Why Corporate AI Projects Fail? Part 2/4                                       
  25. TLDR: AI for Text Summarization & Generation of TLDRs   
  26. Covid or just a Cough? AI for Detecting Covid-19 from Cough Sounds 
  27. Using Bash to Read Files
  28. Reskilling India for an AI-First Economy                                                     
  29. Fact-checking Covid-19 Fake News                                            
  30. AI-enabled Conversations with Analytics Tables
  31. [Video] Q&A on Careers in AI (Industry Insiders for UCL Alumni)
  32. How do I crack data science interviews, and should I learn DSA for the same?
  33. [Video] Robinhood Machine Learning System Design Mock Interview
  34. [Video] Amazon Deep Learning Mock Interview
  35. [Video] AI in India (Industry Insiders for UCL Alumni)
  36. [Video] Careers in AI
  37. [Video] AI Career Advice - Part 1
  38. [Video] AI Career Advice - Part 2
  39. [Video] ​How to conduct innovative, applied AI research?
  40. [Video] How has the field of AI evolved?
  41. Advice for people who want to do research in AI
  42. How crucial is starting early for those interested in data science?

What my clients are saying?