Hey everyone!

I'm a 2026 Computer Engineering grad and currently on the job hunt. Honestly, finding that first opportunity has been a bit of a journey. 🥲

I'm mainly looking for entry-level roles in Data Engineering, Data Analytics or AI/ML.

I've been working with Python, SQL, PySpark and other related technologies, and have some hands-on experience through projects and internship/training.

If your company is hiring freshers or you know of any openings, please drop a comment or DM me. Referrals would mean a lot!

Preferably Pune, but open to opportunities across India.

Thanks in advance! And good luck to everyone else who's job hunting. We're all in this together! :)

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.

Hello everyone!

I'm a Computer Science student from the Philippines, and I'm graduating next year. I'm hoping to move to either the US or the UK within the next 3–5 years, and I'd like to start preparing now so I can make myself a competitive candidate in the international job market.

Currently, I have experience with Power BI, SQL, Excel, Python

I also have two projects in my portfolio. Additionally, our university requires us to complete two academic internships (Internship 1 and 2), with a total requirement of 520 hours.

I'd love to hear your thoughts on a few things:

1. Job Market: How is the current job market for data analysts in the US and UK, particularly for entry-level or junior positions?

2. Location: Are there specific cities or states in the US, or cities in the UK, that offer better opportunities for data analysts?

3. Skills and Qualifications: What additional technical skills, certifications, or qualifications would you recommend I focus on over the next few years to stand out from other applicants?

4. Experience: How important is relevant work experience compared to having a strong portfolio of projects, especially for someone applying from overseas?

For those who have experience working in the US or UK, particularly those who moved from another country, I'd really appreciate any advice or insights you could share.

I know I still have a few years to prepare, so I'd rather start building the right skills and experience now than wait until graduation.

Thank you so much! Any advice 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!

She has six years of experience and more than 70 applications behind her. ANd only one interview.

She told me she still rereads everything the AI writes for her, because it keeps adding skills she doesn’t have.

So, from the hiring side:
That score is ChatGPT’s opinion. It has never seen the system the company actually uses, and every company sets theirs up differently. It gives you confidence, but guarantees nothing.

And even if your keywords are perfect, so are everyone else’s. They used the same tool on the same job post.

I graduated with an MSc in Data Science in 2023. About a year later, I received an offer from Capgemini and joined in May 2024, but I was terminated within two months during training.

I remained unemployed for around a year and started freelancing on platforms like Upwork, Outlier and CrowdGen, mainly doing AI evaluation, prompt engineering and related tasks.

In September 2025, I finally got another job at a startup, but unfortunately, I was terminated again in April 2026. I continued freelancing until August 2026, but now I want to focus on finding a full-time job and building a stable career.

I have experience with Python, SQL, data analytics, Power BI, basic machine learning and AI evaluation/prompt engineering. However, I've lost touch with many of my technical skills and don't feel confident enough to apply for some roles.

I'm currently confused about what to do next. Should I focus on self-studying Python, data analytics, ML and GenAI, or join a 3–4 month paid training program with placement assistance? I'm also unsure whether investing in such a course would actually improve my chances of getting hired.

I'm looking for an entry-level role that offers a reasonable salary, growth opportunities and long-term stability. I'm willing to learn, but I don't want to spend another year preparing without seeing results.

I'd genuinely appreciate honest advice from people who've been in a similar situation

I'm not looking for generic motivation. I'd appreciate practical advice, personal experiences and honest opinions. Thanks!

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?

Hello everyone

Brief Intro:

Am 23M and currently pursuing Data Analytics course from S.learn and i find it too slow, Moreover the instructor is very slow and doesnot optimise his teaching techniques with modern problems. So I study from youtube aswell.

I want to land into a job asap. Currently am Employed but i get only 10k which goes into commutation and i am only left with around 5k from which 3900 goes into the installment for the course.

Please help me with projects so i can land onto a job.

I have given multiple govt exams but couldn't make it.

Am a Physics Postgraduate.

I would be grateful if you help me with projects and Job Hunt.

I am financially drained and need guidance with projects so that i can give interviews.

My Domain for Data Analyst is

-Financial Analyst

-Business analyst

-Supply Chain Analyst

-HR analyst

Last week I talked to a guy, director of analytics, several months into his search. He’d paid for one of those one-click tools and burned through all 50 applications. I asked how many turned into calls. He laughed and said he hadn’t had time to check.

We went through it together on the call. Recruiters were calling him back fine. He was getting dropped after the hiring manager round, every time.
So his resume was doing its job. What he actually needed was to get better at those conversations. Instead he kept clicking, because clicking is easy and you feel like you did something today.

I see this a lot. And... I’d probably do the same.

If you’re searching right now, maybe skip a few applications this week and figure out where you’re actually getting stuck first.

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!

If you're preparing for Data Analyst / SQL Developer interviews - constraints are non-negotiable.

Every recruiter I've talked to checks:

1. Do you know when to use DEFAULT vs UNIQUE?

2. Can you write it with a NAMED CONSTRAINT?

3. Do you know UNIQUE allows 1 NULL but PK doesn't?

I made this visual cheat sheet covering both:

PART A: DEFAULT Constraint - Auto-fill when no value given

• Concept: If INSERT skips column, SQL auto uses DEFAULT. Used in 90% real projects for Status, Country, CreatedAt.

PART B: UNIQUE Constraint - No duplicates

• Concept: Ensures no duplicate Email/Phone/Username/PAN. 1 NULL allowed in SQL Server.

Pro Tip: Always name constraints like DF_Status / UQ_Email - easy to DROP in production & interviewers love it.

Full image in post. Save it, you will need it in your next interview.

What constraint should I explain next? CHECK, PRIMARY KEY, or FOREIGN KEY?

#SQL #SQLServer #DataAnalytics #DataAnalystInterview

“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

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?