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Career Advice#LLM Engineering📝 BlogAnalyzed: Jan 3, 2026 07:01

Is it worth making side projects to earn money as an LLM engineer instead of studying?

Published:Dec 30, 2025 23:13
1 min read
r/datascience

Analysis

The article poses a question about the trade-off between studying and pursuing side projects for income in the field of LLM engineering. It originates from a Reddit discussion, suggesting a focus on practical application and community perspectives. The core question revolves around career strategy and the value of practical experience versus formal education.
Reference

“The article is a discussion starter, not a definitive answer. It's based on a Reddit post, so the 'quote' would be the original poster's question or the ensuing discussion.”

Permalinkr/datascience
Research#llm📝 BlogAnalyzed: Dec 29, 2025 09:02

What skills did you learn on the job this past year?

Published:Dec 29, 2025 05:44
1 min read
r/datascience

Analysis

This Reddit post from r/datascience highlights a growing concern in the data science field: the decline of on-the-job training and the increasing reliance on employees to self-learn. The author questions whether companies are genuinely investing in their employees' skill development or simply providing access to online resources and expecting individuals to take full responsibility for their career growth. This trend could lead to a skills gap within organizations and potentially hinder innovation. The post seeks to gather anecdotal evidence from data scientists about their recent learning experiences at work, specifically focusing on skills acquired through hands-on training or challenging assignments, rather than self-study. The discussion aims to shed light on the current state of employee development in the data science industry.
Reference

“"you own your career" narratives or treating a Udemy subscription as equivalent to employee training.”

Permalinkr/datascience
Education#Data Science📝 BlogAnalyzed: Dec 29, 2025 09:31

Weekly Entering & Transitioning into Data Science Thread (Dec 29, 2025 - Jan 5, 2026)

Published:Dec 29, 2025 05:01
1 min read
r/datascience

Analysis

This is a weekly thread on Reddit's r/datascience forum dedicated to helping individuals enter or transition into the data science field. It serves as a central hub for questions related to learning resources, education (traditional and alternative), job searching, and basic introductory inquiries. The thread is moderated by AutoModerator and encourages users to consult the subreddit's FAQ, resources, and past threads for answers. The focus is on community support and guidance for aspiring data scientists. It's a valuable resource for those seeking advice and direction in navigating the complexities of entering the data science profession. The thread's recurring nature ensures a consistent source of information and support.
Reference

“Welcome to this week's entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data science field.”

Permalinkr/datascience
Research#llm📝 BlogAnalyzed: Dec 27, 2025 11:01

Dealing with a Seemingly Overly Busy Colleague in Remote Work

Published:Dec 27, 2025 08:13
1 min read
r/datascience

Analysis

This post from r/datascience highlights a common frustration in remote work environments: dealing with colleagues who appear excessively busy. The poster, a data scientist, describes a product manager colleague whose constant meetings and delayed responses hinder collaboration. The core issue revolves around differing work styles and perceptions of productivity. The product manager's behavior, including dismissive comments and potential attempts to undermine the data scientist, creates a hostile work environment. The post seeks advice on navigating this challenging interpersonal dynamic and protecting the data scientist's job security. It raises questions about effective communication, managing perceptions, and addressing potential workplace conflict.

Key Takeaways

Reference

“"You are not working at all" because I'm managing my time in a more flexible way.”

Permalinkr/datascience
Research#data science📝 BlogAnalyzed: Dec 28, 2025 21:58

Real-World Data's Messiness: Why It Breaks and Ultimately Improves AI Models

Published:Dec 24, 2025 19:32
1 min read
r/datascience

Analysis

This article from r/datascience highlights a crucial shift in perspective for data scientists. The author initially focused on clean, structured datasets, finding success in controlled environments. However, real-world applications exposed the limitations of this approach. The core argument is that the 'mess' in real-world data – vague inputs, contradictory feedback, and unexpected phrasing – is not noise to be eliminated, but rather the signal containing valuable insights into user intent, confusion, and unmet needs. This realization led to improved results by focusing on how people actually communicate about problems, influencing feature design, evaluation, and model selection.
Reference

“Real value hides in half sentences, complaints, follow up comments, and weird phrasing. That is where intent, confusion, and unmet needs actually live.”

Permalinkr/datascience
Research#data science career📝 BlogAnalyzed: Dec 28, 2025 21:58

Weekly Entering & Transitioning - Thread 22 Dec, 2025 - 29 Dec, 2025

Published:Dec 22, 2025 05:01
1 min read
r/datascience

Analysis

This Reddit thread from the r/datascience subreddit serves as a weekly hub for individuals seeking guidance on entering or transitioning into the data science field. It provides a platform for asking questions about learning resources, educational pathways (traditional and alternative), job search strategies, and fundamental concepts. The thread's structure, with its focus on community interaction and readily available resources like FAQs and past threads, fosters a supportive environment for aspiring data scientists. The inclusion of a moderator and links to further information enhances its utility.
Reference

“Welcome to this week's entering & transitioning thread!”

Permalinkr/datascience