Row 6084
Content Data
This page contains data entry 6084 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
A common thing I notice among Data Scientists is that their code is generally questionable, very unoptimised, and always in a Jupyter notebook.
Anything related to deployment or general algorithms are typically ignored
I can understand that in larger companies there are other teams that can take a model or the analysis and handle the engineering, but surely there should be a base knowledge and understanding expected from someone with the title “Data Scientist”?
What are your thoughts? Can a data scientist succeed in a role if they ignore the engineering side?
| Field | Value |
|---|---|
| text | A common thing I notice among Data Scientists is that their code is generally questionable, very unoptimised, and always in a Jupyter notebook. Anything related to deployment or general algorithms are typically ignored I can understand that in larger companies there are other teams that can take a model or the analysis and handle the engineering, but surely there should be a base knowledge and understanding expected from someone with the title “Data Scientist”? What are your thoughts? Can a d… |
| label | r/datascience |
| dataType | post |
| communityName | r/datascience |
| datetime | 2024-05-07 |
| username_encoded | Z0FBQUFBQm5LakwyaEU4eXNick9TTFdONlR5S1RyMmdlMWRqTWNFNnVtRnh1Z1J0VGMyUlBTWmpIb2Mzc09VYXExQlF6LVRYMlZsZDFNSDNnOUEyZjNlNEc5cnE5bGxmNV9BQ3g3YUlNbmEwOVh6R1FfU21admM9 |
| url_encoded | Z0FBQUFBQm5Lak9HNkRrSkE1YzdySzl6ZkJkamRVb2dwQnJReVZjWVVJRVpfS1VOVDVqeVdrcE5YMVFqZDY2b3ZqNGJKNWVvdWJyN3V2Y2ZpQ1kxRDlTc3JBRkh6dVJua0FwQ3U4NzJjUGtwblp1dG9CYWlvMTd3NGJHd3dmMTFMNEp3eEwxRVA5UHk5bmFVQXI1U3c4RmJuZXE4eGlmSjJ4UlZXNDJiU0tKQy0teGhQOEttcGpfUm8xWFZweTJBSkE3eWxNU3FVUnpybkRZYmlTQ2NZamNGaDZ4SmhGWDZ3UT09 |
Raw Record
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"text": "A common thing I notice among Data Scientists is that their code is generally questionable, very unoptimised, and always in a Jupyter notebook.\n\nAnything related to deployment or general algorithms are typically ignored\n\nI can understand that in larger companies there are other teams that can take a model or the analysis and handle the engineering, but surely there should be a base knowledge and understanding expected from someone with the title “Data Scientist”?\n\nWhat are your thoughts? Can a data scientist succeed in a role if they ignore the engineering side?",
"label": "r/datascience",
"dataType": "post",
"communityName": "r/datascience",
"datetime": "2024-05-07",
"username_encoded": "Z0FBQUFBQm5LakwyaEU4eXNick9TTFdONlR5S1RyMmdlMWRqTWNFNnVtRnh1Z1J0VGMyUlBTWmpIb2Mzc09VYXExQlF6LVRYMlZsZDFNSDNnOUEyZjNlNEc5cnE5bGxmNV9BQ3g3YUlNbmEwOVh6R1FfU21admM9",
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}
Entry Information
- Entry ID: 6084
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000