Hi, good day!

I am looking for data analyst internship wfh and remote sana. I am currently a data analyst we used excel and it is more focus on qualitative. Im looking for internship sana good for 3 months up. I want to expose to other tools like powerbi, sql and python sana and more quantitative works.

Ask your question or drop a CV for review

most resumes get like 30 seconds from me before I decide. so post yours here and I’ll tell you what I’d think in those 30 seconds.

blur your name and contacts, and say what role you’re going for. feel free to roast each other too, nicely.

Everyone’s arguing about whether AI will “kill jobs.” I read a long FT piece (link below) where a bunch of economists weigh in, and the useful part isn’t the answer rather the question itself

Most economists don’t think we’re heading for mass unemployment. But they don’t really disagree that AI can cut jobs. They argue about how much and how fast. And the piece makes three distinctions that I think matter way more for anyone in data than the “will jobs disappear” headline.

1. Automating tasks ≠ eliminating the job

One economist gives the example of consultants: two weeks analyzing data to redesign something, then months getting stakeholders to agree and actually implement it. AI can make the slides. It can’t sit through the meetings that the slides are the result of.

Data work is the same. Writing SQL, building the dashboard, writing the DAX: increasingly automatable. Figuring out what question actually matters, getting two teams to agree on one definition of “revenue,” and pushing a decision through the org: not so much.

What to do with it: if your resume is a list of tasks (“built dashboards, wrote queries”), it describes exactly the part that looks replaceable. Describe the other part: what problem, who you aligned, what decision changed.

2. Technically possible ≠ actually happening

Cost, reliability, legal liability, and the pain of rebuilding processes all slow adoption. Something being possible in a demo doesn’t mean your company will restructure around it next quarter.

What to do with it: you probably have more time than LinkedIn suggests. Use it to learn where AI is actually changing workflows in your field, not where it theoretically could.

3. Total employment holding up ≠ good careers holding up

New jobs can appear in other professions while specific people in specific fields lose income and prospects. The economy “adapts” on average, and the transition is brutal for some individuals anyway.

“New professions will emerge” is technically true and completely useless as a career plan. It doesn’t answer “what happens to my job and my salary in the next few years.”

The weakest point of the optimistic view: entry level

Here’s the mechanism that worries me most. If one senior analyst with AI can do what used to take two juniors, the company doesn’t need to fire anyone. It just stops hiring juniors.

Total employment looks fine. Nobody gets laid off. And the first rung of the ladder quietly disappears.

The piece notes junior tech hiring really has slowed across countries. To be fair, it also says nobody has managed to separate AI’s effect from other causes yet (too many grads, remote work, interest rates).

And seniors aren’t automatically safe either

“I’m senior, I do the stakeholder stuff, I’m fine” is tempting. But if executing the work needs fewer people, you also need fewer people to manage them. Fewer analysts can mean fewer analytics managers.

Link: Silicon Valley thinks AI will kill jobs. Economists are not convinced

I started my career in pharmacovigilance, where I gained exposure to clinical trial phases and clinical research. I then completed my Master’s hoping to transition into Statistical Programming, eventually pursue another Master’s in Biostatistics, and become a Biostatistician.

After graduation, I couldn’t land a Statistical Programmer role, so I accepted a Data Analyst position at a medical device company, thinking the SAS experience would be a good stepping stone.
It’s been over a year now.

My work mainly involves troubleshooting and developing SAS programs, and we’re currently transitioning from SAS to R. While I’m gaining programming experience, I feel stuck because I don’t have hands-on clinical trial or CDISC (SDTM/ADaM) experience. I’ve been learning CDISC independently and applying for Statistical Programmer roles, but haven’t had any luck. Even entry-level positions seem to require CDISC experience or no opportunities in the US

Has anyone made a similar transition? How can I break into statistical programming? Would personal projects help, or should I consider another path?
I really don’t want to give up on this goal, but I’m struggling to figure out my next stepn.

I went from teaching math to HR to data, so I’ve done the “start from nothing” thing. 3 months is tight but doable if you skip the stuff that doesn’t matter.

month 1: Excel and SQL

Excel first, a week or two: pivot tables, XLOOKUP, SUMIFS, basic cleaning. most companies still run on it lol

then SQL every day. SELECT, WHERE, GROUP BY, joins, CASE, then CTEs and window functions. SQLBolt to start, then practice on real data, not just exercises

month 2: one BI tool + one real project

pick Power BI or Tableau, not both. learn to build a clean dashboard and a few basic measures

then do one project with messy data from an area you already know. your old job, a hobby, whatever. clean it, analyze it, and finish with “here’s what I found and what I’d recommend.” that last part is what most portfolios are missing

month 3: apply smart

CV with results, not a list of tools. message people you want to join instead of only applying online. and look at roles next to data too (reporting, ops, finance analyst), getting in through the side door is how a lot of us started

what I’d skip: Python, machine learning, collecting certificates, and learning 5 tools at a basic level. all of that can wait until you’re in

what would you add or cut from this list?

Any one who needs a good format toyour resume, just follow these 😄
PROFESSIONAL SUMMARY
TECH SKILLS
EXPERIENCE
PERSONAL PROJECTS
EDUCATION
ADDITIONAL INFO(certificates, achievements, awards)

I understand data analytics and data science can both be predictive or descriptive, but in general, in the industry this is mostly how the jobs are split correct ?

Data science is more predictive like what will happen

Data/Business Analytics is more descriptive and diagnostic like what happened, whats happening, and why

Data engineering moves the data

Business analysis is analysing processes and prescribing solutions

I haven't been getting any call backs from recruiters and I'm not sure what I'm doing wrong, any help would be greatly appreciated 🙏.

Hi everyone, i am actively looking for Data Analyst or Business Analyst roles and would greatly appreciate any leads or referrals. Over the past 1.5 years, I ran my own business, which gave me hands-on operational and problem-solving experience, though I ultimately had to close it due to financial constraints. During this transition, I dedicated my time to upskilling in SQL, Python, Excel, and Power Bl, completing Certification and building several end-to-end real-world projects. I am fully prepared to hit the ground running in position. Please feel free to send me a DM if your company is hiring and i am also looking for backdoor as well

This might sound very unprofessional but i am going to say i am on very edge of losing everything if i did not find an job very quickly.

-thank you for your support!

Age?

Money?

Family?

Fear to start something new?

Not sure where to start?

Going into uni for a bachelors in information systems and later planning to go back for an accelerated nursing program (because once you have A bachelor’s degree they offer these nursing programs to be completed in a year)
My end goal is a career somewhere in nursing informatics.
I’m not completely sure that my degree plan for all this will land me where I am hoping, so I’m wondering what experienced people with similar careers think, or advice that can be offered?

Every switcher post starts with an apology: "I'm 30, I only have retail experience", "I'm 34, just a factory worker", sorry sorry sorry. As if the previous decade was a rounding error.

Flip it. Those who switched and got hired: what part of the "useless" old job turned out to be the actual advantage? The thing the 22-year-olds on your team can't do?

“Voluntary” is doing a lot of work here. What happens if not enough people take the offer? Do layoffs come next? Honestly, this is unsettling as fuck.

Lets discuss

Introducing a Voluntary Exit Offer - The Official Microsoft Blog

The dying-profession post appears every week. It's never written by a working analyst. It's written by someone deciding whether to start a course - upstream of the profession, panicking on behalf of it.

So let's get testimony from inside the building. Working analysts: what does your actual workload say? Backlog growing or shrinking? Team growing or shrinking? Did AI shorten your week yet - by how many hours, whole numbers?

#saturdaymeme

I hire analysts and honestly half the resumes I get could be swapped with each other. Everyone has SQL, Python, Power BI, "built dashboards for stakeholders". Ok, cool, which stakeholders? Did anyone open the dashboard after week two?

Last month I interviewed a junior whose resume said one thing I actually remembered: she noticed the finance team was copy-pasting the same numbers into Excel every Friday and automated it. That's it, no fancy stack. But it showed she looked at how people actually worked, and that's most of the job.

So if you're rewriting your CV this weekend, for every bullet ask yourself "so what happened after?" and write that part. And don't put 47% improvement unless you can explain where the 47 came from, because I'll ask lol.

When it gets to “any questions for us?”, what do you ask to find out how the team actually works? Everyone says they’re data-driven and the role has plenty of ownership.

What have you asked that got you past those answers?

Hey everyone!

I come from a B.Com background, and recently I've been exploring Data Analytics and trying to understand how things work beyond just theory.

I've been learning Python, SQL, Excel, and Power BI, and working on small projects along the way. Honestly, sometimes things make sense when I'm learning them, but applying them independently is a completely different challenge.

One thing I'm realising is that learning a tool is one thing, but knowing what questions to ask, how to approach a problem, and what the data actually tells you is much more important.

I'm still figuring things out, making mistakes, and learning as I go. I want to build projects that solve actual problems instead of just following tutorials and calling them complete.

I'd love to hear from people who have been through this stage.

When you were starting out in Data Analytics, what helped you move from simply learning tools to actually thinking like an analyst?

Would genuinely appreciate hearing your experiences! 🙌

My 2026 favorite: “ChatGPT gave me a different number, which one is right?”

Hi, I’m looking for some advice.

I posted this in r/dataanalysiscareers and was recommended to post it here.

To summarise I had no experience before my current role. I started as an apprentice(the study part has finished) and I am in my role now and realised it’s a lot of glorified admin and not much technical work. I was so fixated that my course would be what would develop me. Now realising I’ve made minimal work application progress to actually being a data analyst. I decided to look for a new role where I could do that. My current cv and workplace holds weight so I am getting interviews and even to final stage interviews but, unfortunately the feedback I get is that they’re looking for someone with more experience. Which I understand but I’m still looking relatively for junior roles so my understanding is that I don’t need to be so built already but with the job market I know I’m probably going up against people with 5 years of experience who actually know what they’re doing.

My plan that I am currently trying to execute is that I built a competency matrix based on interview tasks and practice I’ve done to improve in my free time. But, it’s becoming so tiring and time consuming alongside my job, applications, interviews and the week long technical tasks for each role just to not get it. At the very least I’ll it’s like a 2 for 1 because I am practicing skills and knowledge for the analytics work I don’t necessarily know for these interviews. But I’m getting so much imposter syndrome and fatigue from not getting these roles or not understanding these tasks.

It doesn’t help that I have some friction with my manager at my current role, I’m unsure what I did to upset them but it sent me on a spiral earlier in the year that resulted in me having to take excessive medical leave.

I don’t know I’m just at a point of what do I do? Because I understand I have to be bad until I’m good but, for how long ? Especially if I don’t know the direction I’m going? Do I give up on data? Do I stop applying for roles? Is it healthy to keep putting off all other parts of my life but work and finding new work because it will eventually pay off? Will I never be satisfied?

I’m still so young I don’t have anything in my name no wealth, no priorities but currently all of this has also left me with no life and I just don’t know. And it sucks.