UsesRThinksXGBoostis still kingHas beenasked “isthis AI?”Has aChatGPTProsubscriptionFound outthat yourdataset hasduplicate rowsafter analysisHas usedreinforcementlearningHas copiedcode fromStackOverflowHasneverused gitHas hard-codedsomething“just for thedemo”Studied/studiesdatasciencePrefersTableau toPowerBIHas beenthe onlydata personon a teamKnowsBayestheorem offthe top oftheir headHasworkedremotelyfull-timeHad toexplain p-values to anon-technicalaudienceHas beento a datascienceconferenceThought aproject wouldtake aweek…it tookthree monthsUsesMATLABPrefersMacOSUsesPythonHad a modelworkperfectly…only intrainingWrote an entirefunction, only todiscover there’sa library thatdoes it betterThinks mostAI-generatedimages lookslightly offHastransitionedinto datafrom anotherfieldTuned hyper-parametersfor hours withnoimprovementSomeoneasked you to“just add AI”to a projectUses >4programminglanguagesBuilt adashboardthat no oneever usedPresented amodel/dash-board, only tobe asked for anExcel exportHastrained amodel ona GPUHasbrokenproductionStillusespython 2Tried toexplainoverfitting toyourmanager/clientUsesVisualStudioCodeBelievesfeatureengineering ismore importantthan modelselectionUses ChatGPT(or Gemini/Claude) 3+times per weekHasmanuallycleaned aCSV in ExcelTried toexplain whycorrelation≠ causationSpends moretime wranglingdata thanbuildingmodelsHas Googledtheir ownerrormessageword-for-wordSpeaks>4 naturallanguagesUsesJupyterPreferspytorch totensorflowPrefers shippingsomethingsimple overbuildingsomethingcleverPrefersGemini toChatGPTHas vibecodedsomethingUsesRThinksXGBoostis still kingHas beenasked “isthis AI?”Has aChatGPTProsubscriptionFound outthat yourdataset hasduplicate rowsafter analysisHas usedreinforcementlearningHas copiedcode fromStackOverflowHasneverused gitHas hard-codedsomething“just for thedemo”Studied/studiesdatasciencePrefersTableau toPowerBIHas beenthe onlydata personon a teamKnowsBayestheorem offthe top oftheir headHasworkedremotelyfull-timeHad toexplain p-values to anon-technicalaudienceHas beento a datascienceconferenceThought aproject wouldtake aweek…it tookthree monthsUsesMATLABPrefersMacOSUsesPythonHad a modelworkperfectly…only intrainingWrote an entirefunction, only todiscover there’sa library thatdoes it betterThinks mostAI-generatedimages lookslightly offHastransitionedinto datafrom anotherfieldTuned hyper-parametersfor hours withnoimprovementSomeoneasked you to“just add AI”to a projectUses >4programminglanguagesBuilt adashboardthat no oneever usedPresented amodel/dash-board, only tobe asked for anExcel exportHastrained amodel ona GPUHasbrokenproductionStillusespython 2Tried toexplainoverfitting toyourmanager/clientUsesVisualStudioCodeBelievesfeatureengineering ismore importantthan modelselectionUses ChatGPT(or Gemini/Claude) 3+times per weekHasmanuallycleaned aCSV in ExcelTried toexplain whycorrelation≠ causationSpends moretime wranglingdata thanbuildingmodelsHas Googledtheir ownerrormessageword-for-wordSpeaks>4 naturallanguagesUsesJupyterPreferspytorch totensorflowPrefers shippingsomethingsimple overbuildingsomethingcleverPrefersGemini toChatGPTHas vibecodedsomething

Data Science Bingo! - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Uses R
  2. Thinks XGBoost is still king
  3. Has been asked “is this AI?”
  4. Has a ChatGPT Pro subscription
  5. Found out that your dataset has duplicate rows after analysis
  6. Has used reinforcement learning
  7. Has copied code from Stack Overflow
  8. Has never used git
  9. Has hard-coded something “just for the demo”
  10. Studied/ studies data science
  11. Prefers Tableau to PowerBI
  12. Has been the only data person on a team
  13. Knows Bayes theorem off the top of their head
  14. Has worked remotely full-time
  15. Had to explain p-values to a non-technical audience
  16. Has been to a data science conference
  17. Thought a project would take a week…it took three months
  18. Uses MATLAB
  19. Prefers MacOS
  20. Uses Python
  21. Had a model work perfectly…only in training
  22. Wrote an entire function, only to discover there’s a library that does it better
  23. Thinks most AI-generated images look slightly off
  24. Has transitioned into data from another field
  25. Tuned hyper-parameters for hours with no improvement
  26. Someone asked you to “just add AI” to a project
  27. Uses >4 programming languages
  28. Built a dashboard that no one ever used
  29. Presented a model/dash-board, only to be asked for an Excel export
  30. Has trained a model on a GPU
  31. Has broken production
  32. Still uses python 2
  33. Tried to explain overfitting to your manager/client
  34. Uses Visual Studio Code
  35. Believes feature engineering is more important than model selection
  36. Uses ChatGPT (or Gemini/ Claude) 3+ times per week
  37. Has manually cleaned a CSV in Excel
  38. Tried to explain why correlation ≠ causation
  39. Spends more time wrangling data than building models
  40. Has Googled their own error message word-for-word
  41. Speaks >4 natural languages
  42. Uses Jupyter
  43. Prefers pytorch to tensorflow
  44. Prefers shipping something simple over building something clever
  45. Prefers Gemini to ChatGPT
  46. Has vibe coded something