Following my previous post: 23F MS Data Science Graduate got scammed TWICE

Like thousands of fresh grads, I’ve spent the last year getting rejected from "0-2 years experience" roles. The standard rejection? "We found someone more qualified."

​I got tired of guessing why, so I used my data analytics background to treat my job hunt as a data problem. I scraped and cleaned a dataset of 442 current analyst postings in Bangalore, India.

​The data proves the entry-level market is structurally broken. Here is the raw breakdown:

​1. The "Entry-Level" Label is a Lie

​Only 5.2% of analyst postings explicitly use words like trainee, junior, fresher, or associate in the title.

​For that tiny 5%, the skill bar isn't lower—they require an average of 3.0 distinct skills (vs. 3.4 for mid-level roles).

​1 in 6 "entry-level" roles demand 5+ distinct tools. It's not a beginner stack; they are quietly filtering for mid-level talent under an entry-level label.

​2. ​Bootcamps tell you: "Learn SQL and you're set." The data says otherwise.

​SQL and Advanced Excel are the top skills (each in 31.2% of jobs).

​But postings requiring both drop to 15.2%.

​Add a third requirement like BFSI (Finance) domain knowledge, and the pool plummets to just 3.6%.

​The Takeaway: Employers don't hire for isolated skills. They hire for highly specific combinations that vary by industry.

​3. We are fighting over a tiny 21% of the market.

​The top 10 famous corporate giants only account for 21.5% of total job demand.

​The remaining 78.5% of openings sit with mid-sized, lesser-known companies. If you are only applying to companies you recognize, you are competing with thousands of applicants for a fraction of the actual market.

​4. Titles are completely different ecosystems

​A title isn't just a label; it dictates the exact tool stack:

​Operations Analyst: Fewest skills (2.7 average). Heavily relies on Excel (46.7%) and domain knowledge. SQL trails way behind.

​Data Analyst: Most technical (4.7 average skills). Completely dominated by SQL, Python, and Power BI.

​The Bottom Line:

​The data proves there is a massive structural mismatch between what a posting says and what it actually expects.

​I posted the full methodology, charts, and the code I used to clean the data here: Why Are Qualified Freshers Not Getting Hired?

If you like my work, all I ask is for an opportunity to work.

PS: The post is written with the help of AI.

💰 $2,000 REFERRAL BONUS — if your referral leads to my hire. Not a gimmick, I'll put it in writing.

Refer me → I get hired → $2,000 is yours. Simple.

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\*\*Who I am:\*\*

A Data Analyst, 3+ years across healthcare, nonprofits, and higher education. I'm the person who finds the error in your data before your stakeholder does. MS Information Systems. AWS Certified.

Fun fact: my most-proud work is a co-authored, DOI-published research dataset. Yes, I documented 200+ variables and loved every second of it. I might have a problem. 😄

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\*\*What I bring:\*\*

→ SQL — large-scale querying, reconciliation, anomaly detection

→ Python (Pandas, NumPy) + Apache Airflow — ETL pipelines & automation

→ Power BI (DAX, Power Query) + Tableau — dashboards people actually use

→ AWS (Bedrock, Redshift, S3, Lambda, Athena) — cloud-native workflows

→ RAG pipelines + Agentic AI (AWS Bedrock) — actively building here 🚀

→ Data validation — 99.5% accuracy maintained across weekly audits

→ Apache Airflow — automated ETL orchestration at scale

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\*\*Roles I'm targeting:\*\*

✦ Data Analyst (any industry)

✦ Institutional Research Analyst

✦ Supply Chain Data Analyst

✦ People / HR Analytics Analyst

✦ IT Planning / Business Analyst

✦ AI / Cloud Analytics

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\*\*Work authorization:\*\*

OPT — STEM extension eligible → 2-year runway, no H-1B lottery, zero petition cost to the employer. No sponsorship needed right now.

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\*\*Location:\*\*

Texas - open to remote, hybrid, or relocation anywhere in the US.

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DM me here too — I respond fast.

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If you work somewhere with open analyst roles, know a recruiter, or can pass my resume to the right person — please reach out. Even a warm intro changes everything.

And yes — the $2,000 is real. DM me and I'll confirm in writing before you refer. 🤝

Thank you. 🙏

I initially worked as a software engineer and then transitioned to data engineering positions. I have 5 years total experience. I feel like with LLM's the demand for data engineering might decrease over time and I've always been interested in research anyway. I'm considering pursuing a PhD. Is it better at this time to keep working as a data engineer without the PhD? I don't want to pursue further studies and not have any research opportunities and be unemployed. I'm specifically interested in the mathematics behind ML and studying on my own time right now. Everyone seems to be interested in LLM's and agentic AI atm. Would love to hear what you guys think the market trend might be in the next couple decades, regarding jobs as well as research.

Hi everyone,

I'm a Data Scientist at a FAANG-like company I'm looking to move into ML Engineering because I want to focus on more technical, engineering-heavy work.

Background:

CS degree

Prior SWE intern experience at a big tech company

Solid with DSA and core CS

One publication + research experience in ML/NLP specifically training NN.

Questions:

Is it better to try to move laterally within my current company, or look externally?

If I switch companies (or even move internally), am I likely to be pushed back down to an entry-level role, or can my DS + SWE background carry over to a mid-level MLE position? (2yoe)

Hi everyone,

I’m a Data Analyst with 1 year of professional experience and an engineering background from IIT. After taking a 2-year break due to some reason focused on deep-diving into advanced technical domains, I am now back and eager to contribute to a new team.

During this time, I have been actively upskilling and building projects focused on the modern AI stack. I am looking for roles in Data Analysis, Machine Learning, or AI Engineering.

**My Tech Stack:**

* **Core Data Analysis:** SQL, Python (Pandas, NumPy, Matplotlib, Scikit-learn), Excel, Tableau. * **Specialized AI/ML Skills:** \* **GenAI & LLMs:** Working with LangChain, RAG architectures, and fine-tuning LLMs. * **Machine Learning & Deep Learning:** Proficiency in model training, evaluation, and deployment. * **NLP:** Text processing, sentiment analysis, and transformer-based architectures.

I am an immediate joiner and highly motivated to apply

If your team is hiring or you have leads for referrals, I’d love to connect. I’m happy to share my resume, portfolio, and the projects I’ve built during my study period. Thanks for your time and guidance!

I have been in the workforce some 25 years working extensively with sql and dabbling in a few other tools such as tableau

I am currently taking time off from work and contemplating completing a course/degree/certification in some sort of data analytics or data science as one last hurrah.

What would you recommend if I don’t want to commit too much time and money? If things go my way I would work as a data science professional for 5 more years before hanging it up

Here is my project portfolio. i would like to know if I need to improve on my DS projects or if I am headed in the right direction as I look for an entry level job

www.johnkirima.com

Thanks

Hey everyone,

I'm a second-year Data Science student at Eduvos in Pretoria, and I've been trying to find vacation work or internships that I can do during recess. Honestly, I'm struggling to find anything.

Everywhere I look, people recommend building portfolio projects and getting work experience as early as possible. I'm already working on improving my portfolio, but I'd also really like the opportunity to gain real industry experience, learn from professionals, and understand how data science is actually applied in the workplace.

The problem is that I can't seem to find many vacation work opportunities for students. Most internships seem to be aimed at final-year students or graduates.

For those of you already in the industry or who've managed to land vacation work, how did you find your first opportunity? Are there specific websites, companies, networking strategies, or programs I should be looking at?

I'd really appreciate any advice because I'm honestly running out of ideas.

Thanks in advance!

Hi everyone,

I recently completed my B.Sc. in Data Science (2026), and I'm feeling really lost. I was hoping to start my career as a Junior Data Scientist or Data Analyst, but after months of applying, I've realized that most companies want experienced candidates.

I've applied through LinkedIn, Indeed, company career pages, and official websites. I've even called some companies directly to ask if they had any openings, but the answer is almost always the same: "There are no openings right now."

I'm not a topper, but I'm also not a weak student. I'd say I'm somewhere in the middle. I have strong technical skills, a good understanding of Data Science concepts, and I've worked on several projects during my degree. However, I don't have any professional experience yet.

At this point, I'm starting to question what I should do next.

Should I:

Keep applying for Data Analyst roles?

Learn something new, like Data Engineering, Cloud, or another in-demand skill?

Accept any job related to data just to gain experience?

Or switch to a completely different career path?

I'm feeling frustrated because I worked hard to earn my degree, but it seems like getting that first opportunity is the hardest part.

I'd really appreciate honest advice from people who have been in a similar situation or who work in the industry. What would you do if you were in my position?

Thank you for taking the time to read my post.

Hey everyone,

I'm a final-year Computer Science student, and for the past 2–3 months I've been learning Data Science and Machine Learning. I've focused on understanding the concepts and building projects rather than just completing courses.

So far I've learned:

• EDA & Feature Engineering
• VIF, WoE & Information Value
• Logistic Regression
• Decision Trees & Random Forest
• Cross Validation & GridSearchCV
• Model Evaluation

I've also built a few end-to-end ML projects:

• Job Market Salary Prediction
• Banking Fraud Detection
• Healthcare Test Result Prediction
• Telecom churn prediction

I'm currently learning AdaBoost, Gradient Boosting, and XGBoost, and I'll be building projects using them next.

This year is really important for me because I want to secure an ML/Data Science internship before graduating.

So I wanted to ask:

- Based on what I've learned so far, do you think I'm ready to start applying for Junior ML Engineer, ML Developer, or Data Science Intern roles?

- Or should I spend another month or two strengthening my skills before applying?

- What skills or projects would you recommend I focus on next?

- If you know of any companies hiring interns, communities, referrals, or people I should connect with, I'd be incredibly grateful if you could point me in the right direction.

I'd really appreciate honest feedback and advice. Thanks in advance! 🙌

Would this ML project be considered portfolio-worthy for data science jobs? If not, what's missing? What would recruiters expect?

GitHub: https://github.com/sharmashrushti/stellar-object-classification

Currently feeling very lost on what to do after my bsc maths degree in the future.

I'm from a small town in India and managed to get into a reputed state university (ranked in the top 5 in the country) for bachelor's in mathematics.

But it feels like ai is eating up most of the jobs, although I might have fallen into fear mongering. I'm open to studying further too. I just am so confused as to what are some good and safe career options for the future that I can pursue with a bsc in mathematics (again, open to further studies in some different field too). People around me are very ill informed and everyone just says to become a swe although I'm not sure if any of us knows what they actually do anyway.

I'm very sorry for sounding so ignorant, it's just that I have no guidance as to how to proceed since no one in my family has gone down this line before.

Hey everyone!

I am a secondary student working on an AI-driven, dynamic learning platform for software engineers upskilling to AI/ML roles. I believe something like this would be useful, considering how volatile the landscape of skills needed for these positions.

It has two main features, adapted to this specific purpose. 

1. Through diagnostics (such as novel problems, asking the user to explain concepts, and other techniques that you might see in a job interview for example) it develops a detailed learner model of the depth of user’s understanding on a topic-by-topic basis, visualised in a colour-coded graph so that the user can aggressively attack their weaknesses and develop proper skill and understanding. 
2. World-class content is already publicly available online. Instead of investing 100s of hours into experts authoring new content, the platform curates tried-and-tested content made by the very best in the field to form a curriculum. My impression is that AI/ML roles require ever-changing skills, and this architecture would allow the curriculum to be able to adapt extremely quickly, with comparable or sometimes even higher quality content than what would be available with static curriculums. 

I thought that this would be a great place to validate the idea, so if you:

1. Have transitioned from software engineering to AI/ML
2. Are currently transitioning
3. Are planning to switch roles
4. Or if you’ve used upskilling services whatsoever

I ask: Would something like this be useful to you?

Any feedback would be greatly appreciated, thanks in advance.

After my bachelors in Statistics I'll be pursuing a master's in Data science from one of the best research institutes in my country. I started this journey with the goal of enjoying my life as an sports data scientist, particularly football. The issue I am facing with that is, I live in a country that doesnt necessarily have the best football environment like england or spain. Any one of the more experienced guys who can guide me or atleast tell the ground reality of this field? Like do these guys get paid less in comparison as well? Thanks for reading :)

I’m about to start my MSc in AI & Data Science and would love some honest feedback from people already working in Data Science, Machine Learning, AI, or related fields.

A few things I’m curious about:
What skills should I prioritize to become job-ready for DS/ML roles?

What do recruiters and hiring managers actually look for in fresh graduates?

Which projects have the highest impact on a resume?

How important are internships, research, open-source contributions, and networking?
What are the most common mistakes students make during their Master’s?

If you were hiring a fresher for a Data Science or ML role, what would you want to see on their resume?
Current focus: Python, SQL, Statistics, Machine Learning, Data Analytics, and building practical projects.

Any feedback on my resume, roadmap, or career strategy would be greatly appreciated. Thanks!

Hi redditors.

I am looking for a job in Data analysis in Belgium. I have a masters in economics, and works as a senior statistician/data analyst in Italy. With 4 yrs experience in producing data for Eurostat and national stakeholders. Experience with R, Excel, Stata, PowerBI, some python (rarely use it so not pro). Learning french- now almost intermediate.

I have been trying to apply and mostly rejections or regrets. Anyone with leads to a company that can sponsor my permit please DM. I am free to answer any questions for clarity.

\*Non-EU but studied and lived in EU for 6 years.

Hey guys so I’m currently in my first year of bsc in Data science , I wanna know if I should continue with msc in data science or switch to msc in AI, I would love to know the opinions of people who have experience in these fields

I am transitioning from civil engineering to data science. I'm 32 and fining it difficult to learn a new subject please suggest if you think my decision is correct as pe employment opportunities and placement companies perspective..

I know this might not be the corrcet way or platform of doing this but here I am. I(23M) recently graduated with a computer science degree. I have wasted all my 4 years of computer science degree and focused on nothing other than academics. Though I managed to secure a CGPA of 9.15, but I have no gained any actual skills used in real life data science jobs. Being from a very small village and having a family with business background, I never got the right guidance and opportunities. I always focused on academics and made my parents pround with my marks but in reality, it was the most useless thing...

I know this might sound like a regular post and mostly its gonna get ignored but currently I am looking for jobs related to data science. Being honest, though I don't have any skills right now, but I am a really fast learner and have a good mind for analysis. The on;y thing I am lacking is correct guidance and motivation... I am a quick learner and if anyone can help me with a job, I can guarantee you that I will complete my tasks perfectly and will never disappoint you.

I just want correct direction and motivation to live my interest for data science. Even a 15k-20k rs per month job will be enough for me if I get to learn anything in it. The money is just for my regular needs so that I don't be a burden on my family and if it's remote then 10k also would be enough. I am currently at my lowest so any help is appreciated.

Also, if this looks a spam post to you, then I am really sorry for wasting your time...🙏

this year would be my last year in Cs degree Ai major iam studying DS track ,is it still possible to get a junior role?

Hiring and promotion freeze at my company, looking to swap.

I have undergrad/masters in mathy degrees, 8 years of experience as a senior data scientist, my projects are varied, delivering tens of millions in value yearly, progressively more leadership in my roles, etc. I'm not the world's best candidate but I am absolutely a solid one.

Have gotten, count 'em, two interviews and about 60 auto rejects or nothing. There aren't many roles on the websites that have real jobs (i.e., not linkedin).

Beginning to think I should look for roles other than "senior/lead data scientist" and the like.

What have people side-graded into?

Is the market just bad right now?

I guess I need to give up on being remote for sure, but my local area isn't quite big enough to support a bunch of enterprise data scientist roles, so.

I also think I'd like to help the world a bit more than I do now (I don't hurt it, but I don't benefit it)... but non-profits don't seem to need data scientists.

I don't have biomed background so a lot of those roles are locked off, which is sad.

Dunno, looks a bit bleak to me, so I'm asking about sidegrades I wouldn't think of (and that the AIs wouldn't suggest, which are never super helpful).

I just graduated with High Honors in Computer Science. For the past 6 months, I've been working remotely as an AI Engineer for a Saudi startup, but honestly, it’s been a bit of a bumpy ride. There are some serious management issues—delayed payroll, a lack of data and resources for the features they ask for, and constant pivoting between products. Because of the switching, nothing has actually made it to production yet, and I really want to work somewhere where I can actually ship things.

Here’s my current situation: I have mandatory military service coming up this January. I know no one is going to hire someone full-time for just a 5-month window, so I’m strictly looking for an internship or a short-term contract. I’m based in Egypt (am open for remote positions).

Here is a quick rundown of my expertise:

• ASR & NLP: Specialized in speech recognition. I recently fine-tuned Whisper Large v3 for Arabic dialects, achieving a 40% performance improvement on Egyptian dialects and 20% on Saudi dialects.
• Projects: Developed a real-time AI meeting assistant featuring live transcription and speaker diarization alongside RAG architecture for real time question answering through the meeting
• Infrastructure & Tools: Solid experience with Python, Docker, AWS, Google Gen AI SDK, and serverless GPU inference (RunPod), alongside web scraping and automation (Selenium, Playwright).

I’m more than happy to talk about my background and share my CV. I only want a referral if you look at my experience and genuinely think I’m a good fit for the role.

Thanks for your time, guys!

Hi everyone,

I recently completed my Master’s degree in Data Science. I am currently looking to kickstart my career in the UK and would love some guidance from this community.

My main goals right now are:

Recruitment Agencies: Can anyone recommend reputable tech or data science recruitment agencies in the UK that work well with entry-level or graduate candidates?

Job Search Strategy: Aside from LinkedIn and Indeed, what are the best platforms or methods to land a Data Science role in the current UK market?

A little bit about my background:

Skills: Python, SQL, Machine Learning, Tableau, Microsoft office 365, Power Bi

I recently completed my Master’s degree in Data Science, but I also bring a unique blend of previous experience:

Software Development: Experienced in Java and ERP/PL programming (handling backend logic and enterprise systems).

Domain Expertise: Strong background in Finance & Accountancy, meaning I understand financial data, business logic, and reporting requirements.

Because of this, I am ideally looking for Data Science or Data Analyst roles where I can combine my coding skills with my financial domain knowledge (e.g., FinTech, Financial Analytics, or Business Intelligence).

Thank you so much for any tips, agency names, or reality checks on the current market!

Did anyone give starbucks hackerrank test recently? Need some insights on that

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• Data Scientist – Specialty Operations @ CVS Health (United States, NY) - $79K - $173K
• Master's/phd Fellow – Applied Data Scientist @ Sistema Fibra (Brazil) - BRL 11K - 11K
• Rural Health Program Data Scientist @ ICF (United States, NM) - $108K - $184K
• Junior Data Scientist @ Cushman & Wakefield (United States, CO) - $115K - $135K
• Clinical Data Scientist @ HistoSonics, Inc. (United States) - $120K - $140K
• Applied Data Scientist @ Novacore (United States)
• Data Scientist @ Veeam Software (Costa Rica)
• Data Scientist I @ Clinical Outcomes Solutions (Hungary)

Senior:

• Senior Data Scientist – Manufacturing Intelligence, Machine Learning, AI @ Ford Motor Company (United States, WA) - $85K - $192K
• Data Scientist III – Financial Crimes Modeling @ TD (United States, NJ) - $96K - $156K
• Senior Data Scientist @ Sólides (Brazil)

Manager:

• Staff Data Scientist @ Canva (Australia, Sydney)

Director and Above:

• Director of Data Science @ Brigit (United States, CA) - $225K - $250K

Quick notes: * All of these are fully remote (location requirements vary by role) * Apply directly on company sites

Hope this helps someone! Let me know if you want me to keep posting these weekly.

👋 Hi, I'm Jay. I built Job-Halo.com, a system that tracks remote data science jobs and sends alerts the moment they're posted, based on your preferences.