Row 4943

Row ID: 4943 | Dataset Entry | Axioma AXP Content Repository

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I am new to industry and I don't seem to find a proper answer to this question.

I know Data Scienctist is expected to model. Train models do Post Production Monitoring. Fine-tuning and maybe retraining. Apparently retraining involves a lot of beaurcratic hoops. Maybe some production .

Data engineers would do preprocessing, ETL , building Warehouse ,SQL queries, CI/CD. Pipeline and scraping. To some extent data scientists do it. Dont feel comfortable personally but doable. Not the best coder but good enough to write psuedocode and gpt ky way out

Analysts will do insights and EDA.

THAT PRETTY MUCH COMPLETES A CYCLE. What exactly does an MLE do then . There are many overlaps but what exactly will an MLE do. I think it would entail MLOps and also Data engineering? So like everything

Obviously a company wont have all the roles . its probably one or two teams.

Now moving to Finance there are many Quant researchers , quant analysts. Dont see a lotof content about it. What do those roles ential. Requirements are similar but how does one choose their niche

FieldValue
text I am new to industry and I don't seem to find a proper answer to this question. I know Data Scienctist is expected to model. Train models do Post Production Monitoring. Fine-tuning and maybe retraining. Apparently retraining involves a lot of beaurcratic hoops. Maybe some production . Data engineers would do preprocessing, ETL , building Warehouse ,SQL queries, CI/CD. Pipeline and scraping. To some extent data scientists do it. Dont feel comfortable personally but doable. Not the best co…
label r/datascience
dataType post
communityName r/datascience
datetime 2024-04-24
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Raw Record

{
  "text": "I am new to industry and I don't seem to find a proper answer to this question.  \n\nI know Data Scienctist is expected to model.  Train models do Post Production Monitoring. Fine-tuning and maybe retraining. Apparently retraining involves a lot of beaurcratic hoops. Maybe some production . \n\nData engineers would do preprocessing, ETL , building Warehouse ,SQL queries, CI/CD. Pipeline and scraping.  To some extent data scientists do it.  Dont feel comfortable personally but doable. Not the best coder but good enough to write psuedocode and gpt ky way out \n\nAnalysts will do insights and EDA. \n\n\nTHAT PRETTY MUCH COMPLETES A CYCLE. \nWhat exactly does an MLE do then . There are many overlaps but what exactly will an MLE do.  I think it would entail MLOps and also Data engineering?  So like everything \n\nObviously a company wont have all the roles . its probably one or two teams. \n\n\nNow moving to Finance there are many Quant researchers , quant analysts. Dont see a lotof content about it. What do those roles ential.  Requirements are similar but how does one choose their niche ",
  "label": "r/datascience",
  "dataType": "post",
  "communityName": "r/datascience",
  "datetime": "2024-04-24",
  "username_encoded": "Z0FBQUFBQm5LakwyXy1tNWxCT1NQMGxFbmxMdmFuc25hWGxaOHR3cVg3aWNpVUtSODJONmUtdUlCOVBHQUJnaV9hX3oxTm5Hbk9fQ1RtenpCNVJ6TTZNdUNBdThySHJmMkE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9GS0FwWWcwSTh5V2tYd256WGltTTJBZWJtUlZPQndncWNJNTdHbWpyZVViZEhORUhmRXMtbmMxVWdaLU10ZzZxcVdvaDBGRzkwRU5IUmdNVWV5R2lHRHdpWVYzWlVZU0tNVHViR01uekZpUk1oZWZOcW00eTFNd1BqZU5Da1o4V190TF9KVW53Qm5sdi1sR0JCZy1oZXBOSnVJNXFrUEN2MXpTV2twTHp1R3F5NXVJZTdiZy1jTk5ZWFpzakZDOEpnbGZoQVE2NU5sSHFRVkVEcm9YN1FwQT09"
}
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