Rob Mulla Portfolio
4x Kaggle Grandmaster (Competitions, Datasets, Discussion, Notebooks) and Head of Data Science at Dreadnode, whose public notebooks and livestreams walk through real competition and time-series/EDA work end-to-end.
What makes it work
A breakdown of the choices that make this portfolio stand out.
Grandmaster tier across multiple independent categories
Ranking Grandmaster in datasets, discussion, and notebooks (not just competitions) shows range — recognized for building datasets, explaining ideas, and shipping code, not just winning leaderboards.
Livestreamed and video-walkthrough notebooks
Publishing recorded, real-time problem-solving exposes actual debugging and decision-making — far harder to fake than a cleaned-up final notebook.
Career pivot into applied AI security
Moving from tabular Kaggle work into AI security/red-teaming and continuing to publish shows the portfolio evolves with the field.
What Data Scientists can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Record yourself solving a real problem, not just the final notebook.
Go for breadth across Kaggle categories rather than only competition rank.
Update your specialization as the field moves — a static portfolio reads as dated.
Use EDA notebooks to show judgment (why this feature, why this split), which matters more than final leaderboard score.
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