Category 07
AI & Data Science
ML engineers, data scientists, NLP specialists, computer vision researchers, LLM practitioners turning data into intelligence.
Who should apply
- ML engineers deploying models to production
- Data scientists solving business problems with analytics
- NLP specialists building language models and chatbots
- Computer vision engineers working on detection, segmentation
- LLM practitioners fine-tuning or building RAG systems
What judges look for
- Model deployed to production with measurable business impact
- Novel approach to a difficult ML problem
- Data pipeline or feature engineering that improved model performance
- AI ethics or responsible AI practices implemented
- Open-source contribution or research published
Eligibility
Universal criteria
Experience & leadership
3–5+ years in technology, mid-tier (non-CXO) roles, proven leadership and impact.
Innovation & creativity
Demonstrated problem-solving and creative solutions within your field.
Growth & mentorship
Continuous learning plus developing others through mentorship or training.
Adaptability & resilience
Proven resilience through crises or significant organizational change.
Ethics & responsibility
High ethical standards, diversity & inclusion, community and sustainability work.
Candidates
Nominees in AI & Data Science
Common questions
FAQ
I use pre-trained models — do I qualify?
Yes. Fine-tuning, prompt engineering, and RAG systems are legitimate engineering. Show the impact of your work.
My model is still in research — not deployed yet.
Apply if the research is significant. But deployed-and-impactful scores higher than research-only.
Know someone who deserves this?
Urge them to apply or nominate someone you know
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