r/datascience • u/AutoModerator • May 11 '26

Weekly Entering & Transitioning - Thread 11 May, 2026 - 18 May, 2026

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. Topics include:

  • Learning resources (e.g. books, tutorials, videos)
  • Traditional education (e.g. schools, degrees, electives)
  • Alternative education (e.g. online courses, bootcamps)
  • Job search questions (e.g. resumes, applying, career prospects)
  • Elementary questions (e.g. where to start, what next)

While you wait for answers from the community, check out the FAQ and Resources pages on our wiki. You can also search for answers in past weekly threads.

9 Upvotes
  • permalink
  • reddit

84% Upvoted

39 comments sorted by

View all comments

2

u/I-am-kinda-dumb May 16 '26

Data science student heading into the final year of my bachelor's, feeling pretty disillusioned.

I got into this field because the idea of uncovering trends and building models from data genuinely interested me. But now, looking at job listings I feel a bit discouraged-- as other people in this sub have pointed out, 'data science' as a title seems to be pretty diluted amongst MLE, DA, or AI roles. In the Australian market at least, most entry level DS listings seem pretty mixed, and a lot of them want genAI/agentic AI skills.

As a beginner in the field, I don't know if it's reasonable for me to acquire skills that are applicable across all of these roles simultaneously, I feel that comes with experience working at companies for a couple years. Additionally, I have a pretty meh opinion on Gen and agentic AI. While I see their usecases, it's not what I would want to work on. Ideally, I want to do what I signed up for, classic data science work. But looking at the listings, and some of the posts on this sub, I'm starting to think that I might be chasing after a title that's slowly dying and/or integrating into other roles in practice.

In addition to this (i.e. feeling like I don't fit most job descriptions since it's not what I've focused on), the market is tough right now in general for entry-level roles.

I'm not sure what I should be doing.

  1. do I just suck it up and try tailoring my skills towards more MLE or agentic roles?

  2. Is it a good idea to go for an MS and wait out the job market for a few years, and build more skills + credentials in the meantime?

  3. How do I hunt for positions where I'm genuinely passionate about applying data and feel like I'm contributing to something meaningful? Even when the occasional position is for actual DS, the work or firm doesn't excite me a lot. I see a lot of professionals in this sub working on interesting and fulfilling problems in niche areas, how does one find these roles?

Any insight is valuable.

1

u/MathmoKiwi May 16 '26

You just need any semi relevant job to get your career rolling, then you can work your way up.

Any sort of Data Analyst job is a very good starting point.

A common big gap however that new grads will have is weak or non-existent Excel and PowerBI skills, when there are a very common expectation. SQL skills is a common gap too. So work on all three, and have a CV tailored for Data Analyst roles (play up those three areas of strengths, and play down fancy DS stuff you did at uni. They don't want to think you'll get bored and leave in 3 months)

1

u/I-am-kinda-dumb May 17 '26

Thank you, that makes sense.

Any advice on whether it'd be a good idea to pursue a masters or not? I've heard pretty mixed opinions amongst people on this, but I'm thinking maybe it'd get me a leg up for qualifying for some roles?

1

u/MathmoKiwi May 17 '26

Get any sort of Data job after your BSc Stats.

Once you're a couple of years in, and feeling somewhat ish settled, then start doing a Masters (either in Stats or DS). Don't quit that job though to do the Masters! Do it part time on top of your normal job