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> I believe that people don’t understand that Data Scientists are full stack engineers. What do you mean by "full stack"? I'm sure there's a spectrum of abilit

by d-z-m 3y ago

> I believe that people don’t understand that Data Scientists are full stack engineers. What do you mean by "full stack"? I'm sure there's a spectrum of ability, but frankly where I'm from, "Data Scientist" refers to someone who can use pandas and scikit-learn. Probably from inside a Jupyter notebook.

v3ss0n 3y ago
Machine learning, data science, Deep learning= backend Plotting, Charting ,visualization, = frontend
- blitzar 3y ago
  Truly the modern renaissance people of our era. Leonardo da Vinci and Michelangelo move over - the Data Scientists have arrived.
- code_runner 3y ago
  This is proving the point of the parent comments. My view of the world, and how the general structure is where I work: ML is ml. There is a slew of really complex things that aren’t just model related (ml infra is a monster), but model training and inference are the focus. Backend: building services used by other backend teams or maybe used by the frontend directly. Data eng: building data pipelines. A lot of overlap with backend some days. Frontend: you spend most of the day working on web or mobile technology Others: site reliability, data scientists, infra experts Common burdens are infrastructure, collaboration across disciplines, etc. But ML is not backend. It’s one component. It’s very important in most cases, a kitschy bolt on in other cases. Backend wouldn’t have good models without ML and ML wouldn’t be able to provide models to the world reliably without the other crew members. The fronted being charts is incorrect unless charts are the offering of the company itself
- chucke1992 3y ago
  Running matplotlib is not doing frontend...
hmottestad 3y ago
Maybe she just meant that "data scientists are engineers too", rather than saying that they work on both the ChatGPT web UI and the the machine learning code on the backend.
- airstrike 3y ago
  Wait until they learn the "engineer" in SWE is already a very liberal use of the term....

by d-z-m 3y ago

v3ss0n 3y ago

Machine learning, data science, Deep learning= backend Plotting, Charting ,visualization, = frontend

blitzar 3y ago
Truly the modern renaissance people of our era. Leonardo da Vinci and Michelangelo move over - the Data Scientists have arrived.
code_runner 3y ago
This is proving the point of the parent comments. My view of the world, and how the general structure is where I work: ML is ml. There is a slew of really complex things that aren’t just model related (ml infra is a monster), but model training and inference are the focus. Backend: building services used by other backend teams or maybe used by the frontend directly. Data eng: building data pipelines. A lot of overlap with backend some days. Frontend: you spend most of the day working on web or mobile technology Others: site reliability, data scientists, infra experts Common burdens are infrastructure, collaboration across disciplines, etc. But ML is not backend. It’s one component. It’s very important in most cases, a kitschy bolt on in other cases. Backend wouldn’t have good models without ML and ML wouldn’t be able to provide models to the world reliably without the other crew members. The fronted being charts is incorrect unless charts are the offering of the company itself
chucke1992 3y ago
Running matplotlib is not doing frontend...

hmottestad 3y ago

Maybe she just meant that "data scientists are engineers too", rather than saying that they work on both the ChatGPT web UI and the the machine learning code on the backend.

airstrike 3y ago
Wait until they learn the "engineer" in SWE is already a very liberal use of the term....