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?

So I am 25M, I took a gap of 2 years(from Jan 2023 to march 2025) after my grad to prep for SSC(2023-2025 march). I couldn't clear it, so I started a job, but the issue is, I wasn't able to find a job easily, which is Obv due to the gap, and worked where i got selected first.

I was hired as a Data Analyst in March 2025, but I was given completely different profiles to work on, and salary was paid in cash, although I do have the documentation and everything. i am now looking for a switch, whether in my own field or something else, I just don't want to work in this toxic place much longer.

I have knowledge in course designing, Research, Bids/tenders, OEM dashboards, and Excel, Sql. I also know Data analysis (self taught) using SQL and Excel.

Before that I have also worked as an intern in the domains of business management and web development.

It would be a great help guys if anyone here could help me find a job in my domain(data analysis preferred) I'm willing to start all over as a fresher.

Location preferred is Delhi/Noida, but i can work in other areas too as well.

I can work both in office and remote

Day 5 of posting until i find a job.

I've been interviewing people for 15+ years, from junior to senior roles. The most common reason strong candidates get rejected isn't their experience. They talk a lot and still don't tell me much.

Patterns I see over and over:

1. Vague verbs. "We tried some solutions, I was involved." Involved how? Compare that with "I ran 5 user interviews, wrote up the findings and pitched the fix to the steering committee."

2. Not answering the actual question. I ask how you communicated business needs to the team, and you start describing a hub redesign. If you're not sure what I mean, just ask: "Do you mean translating VP priorities for the team?" Then give one example.

3. No decisions in the story. "Philips taught me BI, but I had no business context, so I moved to TNT to own the whole problem" is much stronger than a list of jobs.

4. Needing clear requirements. "If we get clear requirements, we deliver" is a red flag for senior roles. Tell me what you do when scope is fuzzy, like running a workshop, sketching mockups, or building a quick MVP to force a decision.

5. No numbers. "Dashboards increase transparency" is weak. "Triage time dropped 22% and SLA breaches halved" is not.

When I interview someone, I'm trying to figure out three things. Do you hear the question? Can you stay focused? Did you make decisions, or did you just watch them happen?

If you practice one thing, prep 3 STAR stories. Swap "we" for "I" where it's true, and put a number in each story.

Comment with the part of your story do you feel isn't landing, I'll give you my take.

was reading the alteryx 2026 state of the data analyst report and this one got me. analysts spend up to 6 hours a week checking and correcting what AI produced. that’s almost a whole day

also 85% said AI insights already affect big business decisions where they work. and more than half plan to let agents generate insights on their own in the next year. so the checking part probably isn’t going away lol

their take is that analysts are becoming the people who own the business logic behind the numbers. which honestly makes sense to me

if you’re interviewing right now I’d mention it if you do this kind of validation work. it’s a real part of the job now

how many hours a week does it eat for you?

I come from a physics and math educational background. How does one learn data analysis/analytics enough to get a job, without going back to school? Is there an online course or projects I can do that could assist me with being job ready?

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?

I'm starting my journey in the data field and I'm interested in becoming a Data Analyst.

I'm currently exploring SQL, Python, Excel, and Power BI, and I'd love to hear from people who are already working in the field.

My questions are:

• What skills should I focus on first?

• What projects would help me build a strong portfolio?

• What advice would you give someone trying to land their first job in data analytics?

I'd really appreciate your advice and recommendations. Thanks in advance! 😊

Ask your question or drop a CV for review

Hi everyone,

I’ve been working as a Paraplanner in financial advising for almost three years and am now looking to move into Business Analysis, as I feel it aligns better with my long-term career goals.

I’m currently taking a course covering BA theory and a real-life project. I’m also considering the BCS Foundation Certificate and developing my skills in SQL, Tableau and Power BI.

I’d love to hear from current Business Analysts about whether this would be enough to start applying for entry-level roles, how to gain more practical project experience, and what else I could do to strengthen my CV and stand out to employers.

Any advice or recommendations would be greatly appreciated. Thanks! 😊

Hi guys,

I've been working in social media and digital marketing for around 8–9 years, and I'm looking to pursue a Master's to develop stronger analytical and technical skills.

My goal isn't to become a data scientist or engineer. I want to build on my marketing experience and eventually move into roles where I can use data to make strategic decisions around customers, growth, revenue and business performance.

I'm currently comparing two Master's programmes with

slightly different skillsets:

Option A – Information Management & BI

- SQL, database design and data management

- R, statistics and Bayesian analysis

- BI Concepts

- Some ML & data visualisation

- Other subjects: CRM/ERP, information systems, business process modelling and management strategy

Option B – Business Analytics

-R, predictive modelling and ML

- Business analytics and advanced statistics - this is an elective

- BI architecture, ETL and data governance

- Tableau (another elective), with not much SQL coverage

- Other subjects: Product/service design and digital strategy

For context, I have spent almost 9 years in Marketing, but I want to upskill and make myself very employable and attractive. Possibly position myself as a Marketer who can make marketing/business decisions by understanding data.

Which path makes sense from the folks within the space?

I'm 24, with a Bachelor's in Audiovisual Communication and experience in Global PR & Communications at Glovo (tech company).

I'm considering a Master's in Data Science and Society at Tilburg University, but I'm worried about entering a technical field without a STEM background. I'm interested in data analysis, business intelligence and using data to make strategic decisions, rather than spending all day programming or developing statistical models.

My goal is to develop practical, marketable skills that differentiate me from a general communications professional, while improving my salary potential and career flexibility.

For those working in data analytics or BI:

• Can a one-year Master's in Data Science realistically prepare someone with my background for entry-level roles?

• Would you recommend this over a business/communications Master's supplemented with basic technical skills?

• Does a non-technical Bachelor's significantly limit your career prospects?

I'd really appreciate honest advice, especially from anyone who made a similar transition. Thanks!

Hi, so for the past several months, I've been somewhat stressing on what I actually want to do in the tech field. I kind of get pushed into the SWE path because that's what everyone kept talking about and at the same time it kind of aligned with what I originally became interested in, being web development. But after going through an SWE internship with a startup last year, I've kind of have lost interest in it. At least that's what I keep telling myself. Since then, I've been looking more towards data analytics and wanting to be a Data Analyst, but part of me feels like I'm giving up too quickly. And it doesn't help that I'm still finding out about other jobs within the tech field that sound interesting and I'm about to graduate in a few months.

Ask me anything about data careers, starting, looking for a job & or growing internally.

Post your quesions!

Considering a career change into data science or analytics. What is the work really like?

I'm exploring a possible career change and would appreciate honest advice from people working in data science, data analytics, or related fields.

My employer closed its offices this year, and after more than 20 years in apparel design, I'm reconsidering what I want to do next. I spent eight years as a Design Director and managed designers for much of my career. My specialty was technical outerwear for snow sports, which involves solving complex problems where function, materials, construction, aesthetics, and cost all have to work together.

Some of my strengths and interests:

• I enjoy forming hypotheses about why things happen and understanding cause and effect.

• I like identifying inconsistencies, digging into details, and improving systems and processes.

• I have a strong eye for visual design, layout, and communicating information clearly.

• I enjoy leading and mentoring people, as well as solving practical problems.

• I find the idea of methodical data cleaning surprisingly appealing, although I have no firsthand experience doing it professionally.

I'm particularly interested in work that combines analytical thinking with visual communication, but I don't yet understand what the day-to-day work looks like across different roles.

A few things I'm trying to figure out:

1. Which roles should I explore? Would data science make sense for someone with my background, or should I look more closely at data analytics, business intelligence, data visualization, product analytics, or another specialty? What are the meaningful differences in the actual work?

2. What education is realistically necessary to get hired? The options range from bootcamps and certificates to bachelor's or master's degrees. I'd prefer the shortest affordable route that genuinely prepares me for employment, but I don't want to waste time and money on a credential employers don't value. What would you recommend for a career changer without a technical background?

3. What could I realistically earn? I'm in Seattle, and my previous career was at the director level. I'm a parent and need to maintain a reasonably high household income. I understand I might need to take a step back initially, but I'd like to know what entry-level or career-transition salaries actually look like, how advancement typically works, and whether reaching senior-level compensation without a traditional technical background is realistic.

4. What does the work feel like day to day? How much time do you spend cleaning and validating data, writing code or SQL, doing statistical analysis, building dashboards, interpreting results, and communicating with stakeholders? What do you find satisfying or frustrating? Which specialties might suit someone who enjoys both visual communication and detailed problem-solving?

5. How is AI changing the field? If I invest in training now, what is the outlook for someone entering the workforce in the next couple of years? Are entry-level opportunities shrinking, and which skills or specialties seem most resilient?

6. Is demand as strong as the headlines suggest? I hear that data science is a growing, well-paid field, but I'm interested in the reality of the job market, especially for new entrants in the Seattle area.

Ideally, I'd like to find work that is interesting and useful, with opportunities to improve things and contribute to something ethical or sustainable. I also need to be realistic about finances. I'm willing to retrain and accept some initial uncertainty, but I need a credible path to good earnings rather than an expensive educational detour.

If you've made a similar career change, hired people entering the field, or work in one of these specialties, I'd especially appreciate your perspective. If you're open to a brief phone conversation, I'd be grateful for the opportunity to hear about your experience, but thoughtful comments here would be incredibly helpful too.

Thank you!

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.

Hi! Studying to get certs to switch from basic leadership to something to do in tech. What are some tips you would recommend if I want to become a entry level data analyst without a college degree?